Overview

Dataset statistics

Number of variables38
Number of observations10344
Missing cells169305
Missing cells (%)43.1%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory3.0 MiB
Average record size in memory304.0 B

Variable types

Text23
Categorical8
Numeric6
DateTime1

Alerts

Category has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
Cert Number of People is highly overall correlated with Number of Cabins and 5 other fieldsHigh correlation
Number of Cabins is highly overall correlated with Cert Number of People and 5 other fieldsHigh correlation
Number of beds is highly overall correlated with Number of Cabins and 2 other fieldsHigh correlation
Number of Toilets is highly overall correlated with Number of Cabins and 2 other fieldsHigh correlation
Number of Showers is highly overall correlated with Number of Cabins and 2 other fieldsHigh correlation
Type is highly overall correlated with Fuel TypeHigh correlation
Condition is highly overall correlated with Cert Number of PeopleHigh correlation
CE Design Category is highly overall correlated with Cert Number of People and 1 other fieldsHigh correlation
Number of Bathrooms is highly overall correlated with Cert Number of People and 1 other fieldsHigh correlation
Material is highly overall correlated with Cert Number of PeopleHigh correlation
Propulsion is highly overall correlated with Cert Number of PeopleHigh correlation
Fuel Type is highly overall correlated with TypeHigh correlation
Number of Bathrooms is highly imbalanced (58.3%)Imbalance
Material is highly imbalanced (55.3%)Imbalance
Fuel Type is highly imbalanced (59.4%)Imbalance
Manufacturer has 1390 (13.4%) missing valuesMissing
Boat name has 9031 (87.3%) missing valuesMissing
Year Built has 567 (5.5%) missing valuesMissing
Condition has 6969 (67.4%) missing valuesMissing
Depth has 3110 (30.1%) missing valuesMissing
Displacement has 5293 (51.2%) missing valuesMissing
CE Design Category has 9562 (92.4%) missing valuesMissing
Cert Number of People has 6747 (65.2%) missing valuesMissing
Number of Cabins has 3869 (37.4%) missing valuesMissing
Number of beds has 3937 (38.1%) missing valuesMissing
Hull Color has 7033 (68.0%) missing valuesMissing
Number of Toilets has 8188 (79.2%) missing valuesMissing
Number of Bathrooms has 9881 (95.5%) missing valuesMissing
Number of Showers has 8403 (81.2%) missing valuesMissing
Material has 1832 (17.7%) missing valuesMissing
Fresh Water Cap has 8226 (79.5%) missing valuesMissing
Holding Tank has 9525 (92.1%) missing valuesMissing
Propulsion has 7053 (68.2%) missing valuesMissing
Engine has 809 (7.8%) missing valuesMissing
Engine Performance has 2281 (22.1%) missing valuesMissing
Fuel Capacity has 3530 (34.1%) missing valuesMissing
Fuel Type has 2322 (22.4%) missing valuesMissing
Engine Hours has 5211 (50.4%) missing valuesMissing
Max Speed has 9452 (91.4%) missing valuesMissing
Cruising Speed has 9797 (94.7%) missing valuesMissing
Advertisement Date has 9474 (91.6%) missing valuesMissing
Number of views last 7 days has 363 (3.5%) missing valuesMissing
Comments has 3266 (31.6%) missing valuesMissing
Additional Comments has 7890 (76.3%) missing valuesMissing
Equipment has 4170 (40.3%) missing valuesMissing
Cert Number of People is highly skewed (γ1 = 43.71910328)Skewed
Number of Cabins is highly skewed (γ1 = 26.59907924)Skewed
Number of beds is highly skewed (γ1 = 45.34369068)Skewed
Number of Toilets is highly skewed (γ1 = 29.15550151)Skewed

Reproduction

Analysis started2023-08-24 19:31:54.120263
Analysis finished2023-08-24 19:32:29.293959
Duration35.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Price
Text

Distinct3283
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Memory size80.9 KiB
2023-08-24T15:32:29.709826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length12.544954
Min length10

Characters and Unicode

Total characters129765
Distinct characters36
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2185 ?
Unique (%)21.1%

Sample

1st rowCHF 3.337,-
2nd rowEUR 3.490,-
3rd rowCHF 3.770,-
4th rowDKK 25.900,-
5th rowSEK 35.000,-
ValueCountFrequency (%)
eur 8700
42.0%
chf 1036
 
5.0%
⣠306
 
1.5%
dkk 183
 
0.9%
65.000 87
 
0.4%
45.000 78
 
0.4%
35.000 75
 
0.4%
89.000 71
 
0.3%
75.000 69
 
0.3%
55.000 69
 
0.3%
Other values (2649) 10058
48.5%
2023-08-24T15:32:30.838465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27272
21.0%
. 10874
 
8.4%
10388
 
8.0%
, 10300
 
7.9%
- 10300
 
7.9%
U 8739
 
6.7%
E 8736
 
6.7%
R 8700
 
6.7%
9 6219
 
4.8%
5 5134
 
4.0%
Other values (26) 23103
17.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56693
43.7%
Uppercase Letter 30332
23.4%
Other Punctuation 21174
 
16.3%
Space Separator 10388
 
8.0%
Dash Punctuation 10300
 
7.9%
Lowercase Letter 572
 
0.4%
Currency Symbol 306
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 8739
28.8%
E 8736
28.8%
R 8700
28.7%
C 1036
 
3.4%
F 1036
 
3.4%
H 1036
 
3.4%
K 402
 
1.3%
 306
 
1.0%
D 222
 
0.7%
S 75
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 27272
48.1%
9 6219
 
11.0%
5 5134
 
9.1%
1 3873
 
6.8%
2 3233
 
5.7%
4 2713
 
4.8%
3 2526
 
4.5%
8 2035
 
3.6%
7 1868
 
3.3%
6 1820
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
e 132
23.1%
r 88
15.4%
s 44
 
7.7%
t 44
 
7.7%
u 44
 
7.7%
q 44
 
7.7%
n 44
 
7.7%
o 44
 
7.7%
c 44
 
7.7%
i 44
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 10874
51.4%
, 10300
48.6%
Space Separator
ValueCountFrequency (%)
10388
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10300
100.0%
Currency Symbol
ValueCountFrequency (%)
£ 306
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98861
76.2%
Latin 30904
 
23.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 8739
28.3%
E 8736
28.3%
R 8700
28.2%
C 1036
 
3.4%
F 1036
 
3.4%
H 1036
 
3.4%
K 402
 
1.3%
 306
 
1.0%
D 222
 
0.7%
e 132
 
0.4%
Other values (11) 559
 
1.8%
Common
ValueCountFrequency (%)
0 27272
27.6%
. 10874
 
11.0%
10388
 
10.5%
, 10300
 
10.4%
- 10300
 
10.4%
9 6219
 
6.3%
5 5134
 
5.2%
1 3873
 
3.9%
2 3233
 
3.3%
4 2713
 
2.7%
Other values (5) 8555
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129153
99.5%
None 612
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27272
21.1%
. 10874
 
8.4%
10388
 
8.0%
, 10300
 
8.0%
- 10300
 
8.0%
U 8739
 
6.8%
E 8736
 
6.8%
R 8700
 
6.7%
9 6219
 
4.8%
5 5134
 
4.0%
Other values (24) 22491
17.4%
None
ValueCountFrequency (%)
£ 306
50.0%
 306
50.0%

Category
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size80.9 KiB
Power Boats
10344 

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters113784
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPower Boats
2nd rowPower Boats
3rd rowPower Boats
4th rowPower Boats
5th rowPower Boats

Common Values

ValueCountFrequency (%)
Power Boats 10344
100.0%

Length

2023-08-24T15:32:31.316314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-24T15:32:31.669197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
power 10344
50.0%
boats 10344
50.0%

Most occurring characters

ValueCountFrequency (%)
o 20688
18.2%
P 10344
9.1%
w 10344
9.1%
e 10344
9.1%
r 10344
9.1%
10344
9.1%
B 10344
9.1%
a 10344
9.1%
t 10344
9.1%
s 10344
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82752
72.7%
Uppercase Letter 20688
 
18.2%
Space Separator 10344
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 20688
25.0%
w 10344
12.5%
e 10344
12.5%
r 10344
12.5%
a 10344
12.5%
t 10344
12.5%
s 10344
12.5%
Uppercase Letter
ValueCountFrequency (%)
P 10344
50.0%
B 10344
50.0%
Space Separator
ValueCountFrequency (%)
10344
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 103440
90.9%
Common 10344
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 20688
20.0%
P 10344
10.0%
w 10344
10.0%
e 10344
10.0%
r 10344
10.0%
B 10344
10.0%
a 10344
10.0%
t 10344
10.0%
s 10344
10.0%
Common
ValueCountFrequency (%)
10344
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113784
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 20688
18.2%
P 10344
9.1%
w 10344
9.1%
e 10344
9.1%
r 10344
9.1%
10344
9.1%
B 10344
9.1%
a 10344
9.1%
t 10344
9.1%
s 10344
9.1%
Distinct135
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size80.9 KiB
2023-08-24T15:32:32.047078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length42
Mean length10.521462
Min length3

Characters and Unicode

Total characters108834
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)0.7%

Sample

1st rowMotor Yacht
2nd rowCenter console boat
3rd rowSport Boat
4th rowSport Boat
5th rowClassic
ValueCountFrequency (%)
boat 3441
19.8%
yacht 3014
17.3%
motor 2857
16.4%
sport 1476
8.5%
flybridge 1228
 
7.0%
cabin 714
 
4.1%
trawler 699
 
4.0%
pilothouse 634
 
3.6%
hardtop 524
 
3.0%
console 388
 
2.2%
Other values (90) 2447
14.0%
2023-08-24T15:32:33.161717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 14797
13.6%
t 13063
 
12.0%
a 9700
 
8.9%
r 9199
 
8.5%
7078
 
6.5%
e 5057
 
4.6%
c 4058
 
3.7%
h 4029
 
3.7%
i 3665
 
3.4%
B 3496
 
3.2%
Other values (30) 34692
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 84179
77.3%
Uppercase Letter 17074
 
15.7%
Space Separator 7078
 
6.5%
Other Punctuation 503
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 14797
17.6%
t 13063
15.5%
a 9700
11.5%
r 9199
10.9%
e 5057
 
6.0%
c 4058
 
4.8%
h 4029
 
4.8%
i 3665
 
4.4%
l 3251
 
3.9%
b 2630
 
3.1%
Other values (11) 14730
17.5%
Uppercase Letter
ValueCountFrequency (%)
B 3496
20.5%
M 3058
17.9%
Y 3054
17.9%
S 1566
9.2%
F 1452
8.5%
C 1379
 
8.1%
P 786
 
4.6%
T 726
 
4.3%
H 704
 
4.1%
D 312
 
1.8%
Other values (6) 541
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 417
82.9%
/ 86
 
17.1%
Space Separator
ValueCountFrequency (%)
7078
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 101253
93.0%
Common 7581
 
7.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 14797
14.6%
t 13063
12.9%
a 9700
 
9.6%
r 9199
 
9.1%
e 5057
 
5.0%
c 4058
 
4.0%
h 4029
 
4.0%
i 3665
 
3.6%
B 3496
 
3.5%
l 3251
 
3.2%
Other values (27) 30938
30.6%
Common
ValueCountFrequency (%)
7078
93.4%
, 417
 
5.5%
/ 86
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 14797
13.6%
t 13063
 
12.0%
a 9700
 
8.9%
r 9199
 
8.5%
7078
 
6.5%
e 5057
 
4.6%
c 4058
 
3.7%
h 4029
 
3.7%
i 3665
 
3.4%
B 3496
 
3.2%
Other values (30) 34692
31.9%

Manufacturer
Text

MISSING 

Distinct932
Distinct (%)10.4%
Missing1390
Missing (%)13.4%
Memory size80.9 KiB
2023-08-24T15:32:33.716538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length38
Mean length20.558186
Min length14

Characters and Unicode

Total characters184078
Distinct characters70
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique398 ?
Unique (%)4.4%

Sample

1st rowRigiflex power boats
2nd rowTerhi power boats
3rd rowMarine power boats
4th rowPioner power boats
5th rowLinder power boats
ValueCountFrequency (%)
boats 9040
31.5%
power 8954
31.2%
bã©nã©teau 663
 
2.3%
jeanneau 553
 
1.9%
sunseeker 391
 
1.4%
marine 298
 
1.0%
quicksilver 297
 
1.0%
sea 256
 
0.9%
ray 253
 
0.9%
princess 248
 
0.9%
Other values (997) 7737
27.0%
2023-08-24T15:32:34.856173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 20495
11.1%
19750
10.7%
e 17509
9.5%
a 17369
9.4%
r 14798
 
8.0%
s 12514
 
6.8%
t 12325
 
6.7%
b 9419
 
5.1%
p 9388
 
5.1%
w 9225
 
5.0%
Other values (60) 41286
22.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 149906
81.4%
Space Separator 19750
 
10.7%
Uppercase Letter 12584
 
6.8%
Other Symbol 1330
 
0.7%
Open Punctuation 194
 
0.1%
Close Punctuation 194
 
0.1%
Dash Punctuation 36
 
< 0.1%
Other Number 24
 
< 0.1%
Other Punctuation 23
 
< 0.1%
Decimal Number 19
 
< 0.1%
Other values (4) 18
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 1713
13.6%
S 1443
11.5%
à 1373
10.9%
C 898
 
7.1%
M 817
 
6.5%
P 787
 
6.3%
A 765
 
6.1%
R 735
 
5.8%
J 589
 
4.7%
F 559
 
4.4%
Other values (17) 2905
23.1%
Lowercase Letter
ValueCountFrequency (%)
o 20495
13.7%
e 17509
11.7%
a 17369
11.6%
r 14798
9.9%
s 12514
8.3%
t 12325
8.2%
b 9419
6.3%
p 9388
6.3%
w 9225
6.2%
n 6403
 
4.3%
Other values (16) 20461
13.6%
Other Punctuation
ValueCountFrequency (%)
. 15
65.2%
& 6
 
26.1%
¶ 2
 
8.7%
Other Symbol
ValueCountFrequency (%)
© 1329
99.9%
¦ 1
 
0.1%
Other Number
ValueCountFrequency (%)
² 18
75.0%
¼ 6
 
25.0%
Decimal Number
ValueCountFrequency (%)
2 17
89.5%
3 2
 
10.5%
Space Separator
ValueCountFrequency (%)
19750
100.0%
Open Punctuation
ValueCountFrequency (%)
( 194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Currency Symbol
ValueCountFrequency (%)
¤ 15
100.0%
Modifier Symbol
ValueCountFrequency (%)
¸ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Control
ValueCountFrequency (%)
– 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 162490
88.3%
Common 21588
 
11.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 20495
12.6%
e 17509
10.8%
a 17369
10.7%
r 14798
9.1%
s 12514
 
7.7%
t 12325
 
7.6%
b 9419
 
5.8%
p 9388
 
5.8%
w 9225
 
5.7%
n 6403
 
3.9%
Other values (43) 33045
20.3%
Common
ValueCountFrequency (%)
19750
91.5%
© 1329
 
6.2%
( 194
 
0.9%
) 194
 
0.9%
- 36
 
0.2%
² 18
 
0.1%
2 17
 
0.1%
¤ 15
 
0.1%
. 15
 
0.1%
¼ 6
 
< 0.1%
Other values (7) 14
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 181332
98.5%
None 2746
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 20495
11.3%
19750
10.9%
e 17509
9.7%
a 17369
9.6%
r 14798
 
8.2%
s 12514
 
6.9%
t 12325
 
6.8%
b 9419
 
5.2%
p 9388
 
5.2%
w 9225
 
5.1%
Other values (51) 38540
21.3%
None
ValueCountFrequency (%)
à 1373
50.0%
© 1329
48.4%
² 18
 
0.7%
¤ 15
 
0.5%
¼ 6
 
0.2%
¶ 2
 
0.1%
¦ 1
 
< 0.1%
¸ 1
 
< 0.1%
– 1
 
< 0.1%

Model
Text

Distinct7458
Distinct (%)72.1%
Missing3
Missing (%)< 0.1%
Memory size80.9 KiB
2023-08-24T15:32:35.484975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length13.074267
Min length1

Characters and Unicode

Total characters135201
Distinct characters106
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6256 ?
Unique (%)60.5%

Sample

1st rowCAP 400
2nd row400 C
3rd row370 S - Aluboot
4th row10 Classic Special Edition
5th rowGullholmensnipa 21
ValueCountFrequency (%)
fly 443
 
1.6%
340
 
1.3%
sport 282
 
1.0%
open 275
 
1.0%
ht 220
 
0.8%
flyer 202
 
0.8%
fisher 199
 
0.7%
cruiser 197
 
0.7%
antares 195
 
0.7%
merry 184
 
0.7%
Other values (4554) 24391
90.6%
2023-08-24T15:32:36.638603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16705
 
12.4%
e 5646
 
4.2%
0 5290
 
3.9%
a 5166
 
3.8%
r 5155
 
3.8%
A 4166
 
3.1%
S 3975
 
2.9%
o 3882
 
2.9%
E 3793
 
2.8%
5 3747
 
2.8%
Other values (96) 77676
57.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 47762
35.3%
Uppercase Letter 42777
31.6%
Decimal Number 25948
19.2%
Space Separator 16710
 
12.4%
Other Punctuation 1159
 
0.9%
Dash Punctuation 452
 
0.3%
Close Punctuation 120
 
0.1%
Open Punctuation 120
 
0.1%
Math Symbol 34
 
< 0.1%
Other Number 30
 
< 0.1%
Other values (5) 89
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 4166
 
9.7%
S 3975
 
9.3%
E 3793
 
8.9%
R 3539
 
8.3%
C 3197
 
7.5%
T 2609
 
6.1%
O 1931
 
4.5%
I 1895
 
4.4%
N 1756
 
4.1%
L 1755
 
4.1%
Other values (18) 14161
33.1%
Lowercase Letter
ValueCountFrequency (%)
e 5646
11.8%
a 5166
10.8%
r 5155
10.8%
o 3882
 
8.1%
t 3729
 
7.8%
i 3521
 
7.4%
n 3107
 
6.5%
s 2388
 
5.0%
l 2252
 
4.7%
u 1835
 
3.8%
Other values (17) 11081
23.2%
Other Punctuation
ValueCountFrequency (%)
. 683
58.9%
, 139
 
12.0%
/ 96
 
8.3%
' 63
 
5.4%
" 57
 
4.9%
! 26
 
2.2%
# 21
 
1.8%
? 19
 
1.6%
% 16
 
1.4%
& 14
 
1.2%
Other values (4) 25
 
2.2%
Decimal Number
ValueCountFrequency (%)
0 5290
20.4%
5 3747
14.4%
2 3322
12.8%
3 2816
10.9%
4 2539
9.8%
1 2002
 
7.7%
6 1987
 
7.7%
8 1709
 
6.6%
7 1558
 
6.0%
9 978
 
3.8%
Control
ValueCountFrequency (%)
œ 5
23.8%
Ÿ 5
23.8%
„ 5
23.8%
€ 2
 
9.5%
“ 1
 
4.8%
‚ 1
 
4.8%
™ 1
 
4.8%
Â… 1
 
4.8%
Math Symbol
ValueCountFrequency (%)
+ 29
85.3%
| 2
 
5.9%
< 2
 
5.9%
¬ 1
 
2.9%
Other Symbol
ValueCountFrequency (%)
© 25
89.3%
® 2
 
7.1%
¦ 1
 
3.6%
Modifier Symbol
ValueCountFrequency (%)
¨ 8
80.0%
¸ 1
 
10.0%
` 1
 
10.0%
Space Separator
ValueCountFrequency (%)
16705
> 99.9%
  5
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
¤ 24
82.8%
Â¥ 5
 
17.2%
Dash Punctuation
ValueCountFrequency (%)
- 452
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Other Number
ValueCountFrequency (%)
¼ 30
100.0%
Other Letter
ValueCountFrequency (%)
º 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 90540
67.0%
Common 44661
33.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5646
 
6.2%
a 5166
 
5.7%
r 5155
 
5.7%
A 4166
 
4.6%
S 3975
 
4.4%
o 3882
 
4.3%
E 3793
 
4.2%
t 3729
 
4.1%
R 3539
 
3.9%
i 3521
 
3.9%
Other values (46) 47968
53.0%
Common
ValueCountFrequency (%)
16705
37.4%
0 5290
 
11.8%
5 3747
 
8.4%
2 3322
 
7.4%
3 2816
 
6.3%
4 2539
 
5.7%
1 2002
 
4.5%
6 1987
 
4.4%
8 1709
 
3.8%
7 1558
 
3.5%
Other values (40) 2986
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134940
99.8%
None 261
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16705
 
12.4%
e 5646
 
4.2%
0 5290
 
3.9%
a 5166
 
3.8%
r 5155
 
3.8%
A 4166
 
3.1%
S 3975
 
2.9%
o 3882
 
2.9%
E 3793
 
2.8%
5 3747
 
2.8%
Other values (73) 77415
57.4%
None
ValueCountFrequency (%)
à 124
47.5%
¼ 30
 
11.5%
© 25
 
9.6%
¤ 24
 
9.2%
¶ 8
 
3.1%
¨ 8
 
3.1%
œ 5
 
1.9%
  5
 
1.9%
Ÿ 5
 
1.9%
Â¥ 5
 
1.9%
Other values (13) 22
 
8.4%

Boat name
Text

MISSING 

Distinct1258
Distinct (%)95.8%
Missing9031
Missing (%)87.3%
Memory size80.9 KiB
2023-08-24T15:32:37.391357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length10.991622
Min length1

Characters and Unicode

Total characters14432
Distinct characters84
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1220 ?
Unique (%)92.9%

Sample

1st rowL'ANTONIN
2nd rowschöner IBIS II mit führerschein
3rd rowHille Roda 16, nettes Einsteiger
4th rowBetty Jean
5th rowFletcher Arrowflyte mit Johnson
ValueCountFrequency (%)
ii 52
 
2.1%
mit 47
 
1.9%
iii 20
 
0.8%
2 19
 
0.8%
sea 18
 
0.7%
la 18
 
0.7%
motoryacht 17
 
0.7%
ak 17
 
0.7%
maxima 16
 
0.6%
de 15
 
0.6%
Other values (1722) 2292
90.6%
2023-08-24T15:32:38.771918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1227
 
8.5%
e 864
 
6.0%
a 753
 
5.2%
A 640
 
4.4%
r 570
 
3.9%
i 558
 
3.9%
t 481
 
3.3%
I 469
 
3.2%
o 465
 
3.2%
E 432
 
3.0%
Other values (74) 7973
55.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6526
45.2%
Uppercase Letter 5555
38.5%
Space Separator 1227
 
8.5%
Decimal Number 898
 
6.2%
Other Punctuation 83
 
0.6%
Open Punctuation 48
 
0.3%
Close Punctuation 35
 
0.2%
Dash Punctuation 30
 
0.2%
Other Number 14
 
0.1%
Currency Symbol 8
 
0.1%
Other values (4) 8
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 640
 
11.5%
I 469
 
8.4%
E 432
 
7.8%
S 382
 
6.9%
M 337
 
6.1%
R 317
 
5.7%
O 314
 
5.7%
L 310
 
5.6%
N 290
 
5.2%
T 266
 
4.8%
Other values (17) 1798
32.4%
Lowercase Letter
ValueCountFrequency (%)
e 864
13.2%
a 753
11.5%
r 570
 
8.7%
i 558
 
8.6%
t 481
 
7.4%
o 465
 
7.1%
n 426
 
6.5%
l 346
 
5.3%
s 305
 
4.7%
u 242
 
3.7%
Other values (16) 1516
23.2%
Decimal Number
ValueCountFrequency (%)
0 179
19.9%
2 130
14.5%
4 94
10.5%
3 94
10.5%
1 90
10.0%
5 77
8.6%
8 68
 
7.6%
7 59
 
6.6%
6 57
 
6.3%
9 50
 
5.6%
Other Punctuation
ValueCountFrequency (%)
' 28
33.7%
, 20
24.1%
" 14
16.9%
. 11
 
13.3%
¶ 5
 
6.0%
/ 2
 
2.4%
? 1
 
1.2%
! 1
 
1.2%
# 1
 
1.2%
Other Number
ValueCountFrequency (%)
¼ 13
92.9%
³ 1
 
7.1%
Modifier Symbol
ValueCountFrequency (%)
´ 1
50.0%
` 1
50.0%
Space Separator
ValueCountFrequency (%)
1227
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Currency Symbol
ValueCountFrequency (%)
¤ 8
100.0%
Control
ValueCountFrequency (%)
Ÿ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Other Symbol
ValueCountFrequency (%)
© 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12081
83.7%
Common 2351
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 864
 
7.2%
a 753
 
6.2%
A 640
 
5.3%
r 570
 
4.7%
i 558
 
4.6%
t 481
 
4.0%
I 469
 
3.9%
o 465
 
3.8%
E 432
 
3.6%
n 426
 
3.5%
Other values (43) 6423
53.2%
Common
ValueCountFrequency (%)
1227
52.2%
0 179
 
7.6%
2 130
 
5.5%
4 94
 
4.0%
3 94
 
4.0%
1 90
 
3.8%
5 77
 
3.3%
8 68
 
2.9%
7 59
 
2.5%
6 57
 
2.4%
Other values (21) 276
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14366
99.5%
None 66
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1227
 
8.5%
e 864
 
6.0%
a 753
 
5.2%
A 640
 
4.5%
r 570
 
4.0%
i 558
 
3.9%
t 481
 
3.3%
I 469
 
3.3%
o 465
 
3.2%
E 432
 
3.0%
Other values (66) 7907
55.0%
None
ValueCountFrequency (%)
à 33
50.0%
¼ 13
 
19.7%
¤ 8
 
12.1%
¶ 5
 
7.6%
Ÿ 4
 
6.1%
´ 1
 
1.5%
³ 1
 
1.5%
© 1
 
1.5%

Type
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)0.3%
Missing5
Missing (%)< 0.1%
Memory size80.9 KiB
Used boat,Diesel
4197 
Used boat,Unleaded
1645 
Used boat
1526 
new boat from stock,Unleaded
1132 
new boat from stock
673 
Other values (31)
1166 

Length

Max length29
Median length28
Mean length17.405649
Min length2

Characters and Unicode

Total characters179957
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st rownew boat from stock
2nd rownew boat from stock
3rd rownew boat from stock
4th rownew boat from stock
5th rowUsed boat

Common Values

ValueCountFrequency (%)
Used boat,Diesel 4197
40.6%
Used boat,Unleaded 1645
 
15.9%
Used boat 1526
 
14.8%
new boat from stock,Unleaded 1132
 
10.9%
new boat from stock 673
 
6.5%
new boat from stock,Diesel 298
 
2.9%
new boat on order,Unleaded 149
 
1.4%
, ,Used boat,Unleaded 115
 
1.1%
, ,Used boat,Diesel 86
 
0.8%
Display Model,Unleaded 75
 
0.7%
Other values (26) 443
 
4.3%

Length

2023-08-24T15:32:39.295773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
used 7730
30.0%
boat,diesel 4311
16.7%
boat 3960
15.3%
new 2399
 
9.3%
from 2126
 
8.2%
boat,unleaded 1813
 
7.0%
stock,unleaded 1132
 
4.4%
stock 674
 
2.6%
417
 
1.6%
stock,diesel 298
 
1.2%
Other values (20) 942
 
3.7%

Most occurring characters

ValueCountFrequency (%)
e 26474
14.7%
15465
8.6%
o 15049
 
8.4%
s 14741
 
8.2%
d 14524
 
8.1%
a 13466
 
7.5%
t 12311
 
6.8%
U 10929
 
6.1%
b 10131
 
5.6%
, 8767
 
4.9%
Other values (17) 38100
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 139731
77.6%
Uppercase Letter 15994
 
8.9%
Space Separator 15465
 
8.6%
Other Punctuation 8767
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26474
18.9%
o 15049
10.8%
s 14741
10.5%
d 14524
10.4%
a 13466
9.6%
t 12311
8.8%
b 10131
 
7.3%
l 8245
 
5.9%
n 5872
 
4.2%
i 4927
 
3.5%
Other values (8) 13991
10.0%
Uppercase Letter
ValueCountFrequency (%)
U 10929
68.3%
D 4869
30.4%
M 121
 
0.8%
E 56
 
0.4%
G 16
 
0.1%
H 2
 
< 0.1%
P 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
15465
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8767
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 155725
86.5%
Common 24232
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26474
17.0%
o 15049
9.7%
s 14741
9.5%
d 14524
9.3%
a 13466
8.6%
t 12311
7.9%
U 10929
7.0%
b 10131
 
6.5%
l 8245
 
5.3%
n 5872
 
3.8%
Other values (15) 23983
15.4%
Common
ValueCountFrequency (%)
15465
63.8%
, 8767
36.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 179957
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 26474
14.7%
15465
8.6%
o 15049
 
8.4%
s 14741
 
8.2%
d 14524
 
8.1%
a 13466
 
7.5%
t 12311
 
6.8%
U 10929
 
6.1%
b 10131
 
5.6%
, 8767
 
4.9%
Other values (17) 38100
21.2%

Year Built
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)1.2%
Missing567
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean2004.8307
Minimum1885
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.9 KiB
2023-08-24T15:32:39.807581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1885
5-th percentile1977
Q11999
median2008
Q32017
95-th percentile2020
Maximum2021
Range136
Interquartile range (IQR)18

Descriptive statistics

Standard deviation16.309045
Coefficient of variation (CV)0.0081348738
Kurtosis9.5640223
Mean2004.8307
Median Absolute Deviation (MAD)9
Skewness-2.4263643
Sum19601230
Variance265.98495
MonotonicityNot monotonic
2023-08-24T15:32:40.383399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2020 1306
 
12.6%
2019 688
 
6.7%
2008 478
 
4.6%
2007 411
 
4.0%
2006 407
 
3.9%
2018 361
 
3.5%
2017 326
 
3.2%
2005 325
 
3.1%
2009 315
 
3.0%
2004 287
 
2.8%
Other values (111) 4873
47.1%
(Missing) 567
 
5.5%
ValueCountFrequency (%)
1885 1
 
< 0.1%
1889 2
< 0.1%
1895 1
 
< 0.1%
1897 1
 
< 0.1%
1898 1
 
< 0.1%
1900 1
 
< 0.1%
1901 3
< 0.1%
1902 1
 
< 0.1%
1903 3
< 0.1%
1904 1
 
< 0.1%
ValueCountFrequency (%)
2021 62
 
0.6%
2020 1306
12.6%
2019 688
6.7%
2018 361
 
3.5%
2017 326
 
3.2%
2016 241
 
2.3%
2015 209
 
2.0%
2014 184
 
1.8%
2013 162
 
1.6%
2012 192
 
1.9%

Condition
Categorical

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)0.3%
Missing6969
Missing (%)67.4%
Memory size80.9 KiB
very good
1158 
new
918 
as new
511 
good
432 
well-groomed
225 
Other values (5)
131 

Length

Max length22
Median length13
Mean length6.3291852
Min length3

Characters and Unicode

Total characters21361
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowas new
2nd rownew
3rd rowgood
4th rownew
5th rowwell-groomed

Common Values

ValueCountFrequency (%)
very good 1158
 
11.2%
new 918
 
8.9%
as new 511
 
4.9%
good 432
 
4.2%
well-groomed 225
 
2.2%
used 114
 
1.1%
to be done up 10
 
0.1%
needs a reconditioning 3
 
< 0.1%
for tinkers 3
 
< 0.1%
defect 1
 
< 0.1%
(Missing) 6969
67.4%

Length

2023-08-24T15:32:40.940218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-24T15:32:41.454051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
good 1590
31.3%
new 1429
28.1%
very 1158
22.8%
as 511
 
10.1%
well-groomed 225
 
4.4%
used 114
 
2.2%
to 10
 
0.2%
be 10
 
0.2%
done 10
 
0.2%
up 10
 
0.2%
Other values (6) 16
 
0.3%

Most occurring characters

ValueCountFrequency (%)
o 3659
17.1%
e 3185
14.9%
d 1946
9.1%
g 1818
8.5%
1708
8.0%
w 1654
7.7%
n 1454
 
6.8%
r 1392
 
6.5%
v 1158
 
5.4%
y 1158
 
5.4%
Other values (13) 2229
10.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19428
91.0%
Space Separator 1708
 
8.0%
Dash Punctuation 225
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 3659
18.8%
e 3185
16.4%
d 1946
10.0%
g 1818
9.4%
w 1654
8.5%
n 1454
 
7.5%
r 1392
 
7.2%
v 1158
 
6.0%
y 1158
 
6.0%
s 631
 
3.2%
Other values (11) 1373
 
7.1%
Space Separator
ValueCountFrequency (%)
1708
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 225
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19428
91.0%
Common 1933
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 3659
18.8%
e 3185
16.4%
d 1946
10.0%
g 1818
9.4%
w 1654
8.5%
n 1454
 
7.5%
r 1392
 
7.2%
v 1158
 
6.0%
y 1158
 
6.0%
s 631
 
3.2%
Other values (11) 1373
 
7.1%
Common
ValueCountFrequency (%)
1708
88.4%
- 225
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 3659
17.1%
e 3185
14.9%
d 1946
9.1%
g 1818
8.5%
1708
8.0%
w 1654
7.7%
n 1454
 
6.8%
r 1392
 
6.5%
v 1158
 
5.4%
y 1158
 
5.4%
Other values (13) 2229
10.4%

Length
Text

Distinct1628
Distinct (%)15.8%
Missing10
Missing (%)0.1%
Memory size80.9 KiB
2023-08-24T15:32:42.249800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.5179988
Min length6

Characters and Unicode

Total characters67357
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique543 ?
Unique (%)5.3%

Sample

1st row4.00 m
2nd row4.00 m
3rd row3.69 m
4th row3.00 m
5th row6.30 m
ValueCountFrequency (%)
m 10334
50.0%
9.00 113
 
0.5%
12.00 111
 
0.5%
10.00 107
 
0.5%
11.00 99
 
0.5%
8.00 85
 
0.4%
6.50 85
 
0.4%
6.00 83
 
0.4%
10.50 81
 
0.4%
7.50 77
 
0.4%
Other values (1619) 9493
45.9%
2023-08-24T15:32:43.508396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 10334
15.3%
10334
15.3%
m 10334
15.3%
0 7335
10.9%
1 6761
10.0%
5 3754
 
5.6%
9 2964
 
4.4%
6 2884
 
4.3%
2 2858
 
4.2%
8 2653
 
3.9%
Other values (3) 7146
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36355
54.0%
Other Punctuation 10334
 
15.3%
Space Separator 10334
 
15.3%
Lowercase Letter 10334
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7335
20.2%
1 6761
18.6%
5 3754
10.3%
9 2964
8.2%
6 2884
 
7.9%
2 2858
 
7.9%
8 2653
 
7.3%
7 2593
 
7.1%
3 2298
 
6.3%
4 2255
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 10334
100.0%
Space Separator
ValueCountFrequency (%)
10334
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 10334
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57023
84.7%
Latin 10334
 
15.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 10334
18.1%
10334
18.1%
0 7335
12.9%
1 6761
11.9%
5 3754
 
6.6%
9 2964
 
5.2%
6 2884
 
5.1%
2 2858
 
5.0%
8 2653
 
4.7%
7 2593
 
4.5%
Other values (2) 4553
8.0%
Latin
ValueCountFrequency (%)
m 10334
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67357
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 10334
15.3%
10334
15.3%
m 10334
15.3%
0 7335
10.9%
1 6761
10.0%
5 3754
 
5.6%
9 2964
 
4.4%
6 2884
 
4.3%
2 2858
 
4.2%
8 2653
 
3.9%
Other values (3) 7146
10.6%

Width
Text

Distinct580
Distinct (%)5.6%
Missing63
Missing (%)0.6%
Memory size80.9 KiB
2023-08-24T15:32:44.249162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0013617
Min length6

Characters and Unicode

Total characters61700
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)1.1%

Sample

1st row1.90 m
2nd row1.50 m
3rd row1.42 m
4th row1.00 m
5th row2.50 m
ValueCountFrequency (%)
m 10281
50.0%
2.50 369
 
1.8%
3.00 260
 
1.3%
2.59 216
 
1.1%
2.55 204
 
1.0%
2.54 176
 
0.9%
4.00 170
 
0.8%
3.50 162
 
0.8%
2.00 162
 
0.8%
3.20 139
 
0.7%
Other values (571) 8423
41.0%
2023-08-24T15:32:45.465762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 10281
16.7%
10281
16.7%
m 10281
16.7%
2 5517
8.9%
0 5006
8.1%
5 4282
6.9%
3 4216
6.8%
4 4133
6.7%
9 1804
 
2.9%
6 1635
 
2.6%
Other values (3) 4264
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30857
50.0%
Other Punctuation 10281
 
16.7%
Space Separator 10281
 
16.7%
Lowercase Letter 10281
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5517
17.9%
0 5006
16.2%
5 4282
13.9%
3 4216
13.7%
4 4133
13.4%
9 1804
 
5.8%
6 1635
 
5.3%
8 1500
 
4.9%
1 1438
 
4.7%
7 1326
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 10281
100.0%
Space Separator
ValueCountFrequency (%)
10281
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 10281
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51419
83.3%
Latin 10281
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
. 10281
20.0%
10281
20.0%
2 5517
10.7%
0 5006
9.7%
5 4282
8.3%
3 4216
8.2%
4 4133
8.0%
9 1804
 
3.5%
6 1635
 
3.2%
8 1500
 
2.9%
Other values (2) 2764
 
5.4%
Latin
ValueCountFrequency (%)
m 10281
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 10281
16.7%
10281
16.7%
m 10281
16.7%
2 5517
8.9%
0 5006
8.1%
5 4282
6.9%
3 4216
6.8%
4 4133
6.7%
9 1804
 
2.9%
6 1635
 
2.6%
Other values (3) 4264
6.9%

Depth
Text

MISSING 

Distinct264
Distinct (%)3.6%
Missing3110
Missing (%)30.1%
Memory size80.9 KiB
2023-08-24T15:32:46.149544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0026265
Min length6

Characters and Unicode

Total characters43423
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)0.8%

Sample

1st row0.25 m
2nd row0.75 m
3rd row0.40 m
4th row0.72 m
5th row0.80 m
ValueCountFrequency (%)
m 7234
50.0%
0.90 582
 
4.0%
1.00 580
 
4.0%
0.80 484
 
3.3%
1.10 392
 
2.7%
1.20 386
 
2.7%
0.70 264
 
1.8%
0.50 253
 
1.7%
0.60 219
 
1.5%
1.30 200
 
1.4%
Other values (255) 3874
26.8%
2023-08-24T15:32:47.287180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8804
20.3%
. 7234
16.7%
7234
16.7%
m 7234
16.7%
1 4269
9.8%
5 1892
 
4.4%
9 1212
 
2.8%
2 1203
 
2.8%
8 1123
 
2.6%
3 836
 
1.9%
Other values (3) 2382
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21721
50.0%
Other Punctuation 7234
 
16.7%
Space Separator 7234
 
16.7%
Lowercase Letter 7234
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8804
40.5%
1 4269
19.7%
5 1892
 
8.7%
9 1212
 
5.6%
2 1203
 
5.5%
8 1123
 
5.2%
3 836
 
3.8%
6 824
 
3.8%
7 779
 
3.6%
4 779
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 7234
100.0%
Space Separator
ValueCountFrequency (%)
7234
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 7234
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36189
83.3%
Latin 7234
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8804
24.3%
. 7234
20.0%
7234
20.0%
1 4269
11.8%
5 1892
 
5.2%
9 1212
 
3.3%
2 1203
 
3.3%
8 1123
 
3.1%
3 836
 
2.3%
6 824
 
2.3%
Other values (2) 1558
 
4.3%
Latin
ValueCountFrequency (%)
m 7234
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8804
20.3%
. 7234
16.7%
7234
16.7%
m 7234
16.7%
1 4269
9.8%
5 1892
 
4.4%
9 1212
 
2.8%
2 1203
 
2.8%
8 1123
 
2.6%
3 836
 
1.9%
Other values (3) 2382
 
5.5%

Displacement
Text

MISSING 

Distinct1380
Distinct (%)27.3%
Missing5293
Missing (%)51.2%
Memory size80.9 KiB
2023-08-24T15:32:47.897980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.2514354
Min length4

Characters and Unicode

Total characters36627
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique757 ?
Unique (%)15.0%

Sample

1st row150 kg
2nd row110 kg
3rd row2'000 kg
4th row84 kg
5th row75 kg
ValueCountFrequency (%)
kg 5051
50.0%
12000 50
 
0.5%
14000 45
 
0.4%
1 44
 
0.4%
9000 43
 
0.4%
5000 43
 
0.4%
11000 42
 
0.4%
3000 40
 
0.4%
2 40
 
0.4%
8000 38
 
0.4%
Other values (1371) 4666
46.2%
2023-08-24T15:32:48.988632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9447
25.8%
5051
13.8%
k 5051
13.8%
g 5051
13.8%
1 2360
 
6.4%
5 1762
 
4.8%
2 1616
 
4.4%
3 1134
 
3.1%
4 1125
 
3.1%
6 962
 
2.6%
Other values (4) 3068
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20939
57.2%
Lowercase Letter 10102
27.6%
Space Separator 5051
 
13.8%
Other Punctuation 535
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9447
45.1%
1 2360
 
11.3%
5 1762
 
8.4%
2 1616
 
7.7%
3 1134
 
5.4%
4 1125
 
5.4%
6 962
 
4.6%
8 940
 
4.5%
7 847
 
4.0%
9 746
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
k 5051
50.0%
g 5051
50.0%
Space Separator
ValueCountFrequency (%)
5051
100.0%
Other Punctuation
ValueCountFrequency (%)
' 535
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26525
72.4%
Latin 10102
 
27.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9447
35.6%
5051
19.0%
1 2360
 
8.9%
5 1762
 
6.6%
2 1616
 
6.1%
3 1134
 
4.3%
4 1125
 
4.2%
6 962
 
3.6%
8 940
 
3.5%
7 847
 
3.2%
Other values (2) 1281
 
4.8%
Latin
ValueCountFrequency (%)
k 5051
50.0%
g 5051
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36627
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9447
25.8%
5051
13.8%
k 5051
13.8%
g 5051
13.8%
1 2360
 
6.4%
5 1762
 
4.8%
2 1616
 
4.4%
3 1134
 
3.1%
4 1125
 
3.1%
6 962
 
2.6%
Other values (4) 3068
 
8.4%

CE Design Category
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)0.5%
Missing9562
Missing (%)92.4%
Memory size80.9 KiB
C - Inshore
402 
B - Offshore
272 
D - Sheltered waters
58 
A - Ocean
50 

Length

Max length20
Median length11
Mean length11.887468
Min length9

Characters and Unicode

Total characters9296
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowD - Sheltered waters
2nd rowD - Sheltered waters
3rd rowC - Inshore
4th rowC - Inshore
5th rowC - Inshore

Common Values

ValueCountFrequency (%)
C - Inshore 402
 
3.9%
B - Offshore 272
 
2.6%
D - Sheltered waters 58
 
0.6%
A - Ocean 50
 
0.5%
(Missing) 9562
92.4%

Length

2023-08-24T15:32:49.484472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-24T15:32:49.904335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
782
32.5%
c 402
16.7%
inshore 402
16.7%
b 272
 
11.3%
offshore 272
 
11.3%
d 58
 
2.4%
sheltered 58
 
2.4%
waters 58
 
2.4%
a 50
 
2.1%
ocean 50
 
2.1%

Most occurring characters

ValueCountFrequency (%)
1622
17.4%
e 956
10.3%
r 790
8.5%
- 782
8.4%
s 732
7.9%
h 732
7.9%
o 674
7.3%
f 544
 
5.9%
n 452
 
4.9%
C 402
 
4.3%
Other values (12) 1610
17.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5328
57.3%
Space Separator 1622
 
17.4%
Uppercase Letter 1564
 
16.8%
Dash Punctuation 782
 
8.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 956
17.9%
r 790
14.8%
s 732
13.7%
h 732
13.7%
o 674
12.7%
f 544
10.2%
n 452
8.5%
t 116
 
2.2%
a 108
 
2.0%
l 58
 
1.1%
Other values (3) 166
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
C 402
25.7%
I 402
25.7%
O 322
20.6%
B 272
17.4%
D 58
 
3.7%
S 58
 
3.7%
A 50
 
3.2%
Space Separator
ValueCountFrequency (%)
1622
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 782
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6892
74.1%
Common 2404
 
25.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 956
13.9%
r 790
11.5%
s 732
10.6%
h 732
10.6%
o 674
9.8%
f 544
7.9%
n 452
6.6%
C 402
5.8%
I 402
5.8%
O 322
 
4.7%
Other values (10) 886
12.9%
Common
ValueCountFrequency (%)
1622
67.5%
- 782
32.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1622
17.4%
e 956
10.3%
r 790
8.5%
- 782
8.4%
s 732
7.9%
h 732
7.9%
o 674
7.3%
f 544
 
5.9%
n 452
 
4.9%
C 402
 
4.3%
Other values (12) 1610
17.3%

Cert Number of People
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct25
Distinct (%)0.7%
Missing6747
Missing (%)65.2%
Infinite0
Infinite (%)0.0%
Mean9.3552961
Minimum1
Maximum1200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.9 KiB
2023-08-24T15:32:50.339197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q17
median8
Q310
95-th percentile14
Maximum1200
Range1199
Interquartile range (IQR)3

Descriptive statistics

Standard deviation24.037107
Coefficient of variation (CV)2.5693582
Kurtosis1999.9534
Mean9.3552961
Median Absolute Deviation (MAD)2
Skewness43.719103
Sum33651
Variance577.78252
MonotonicityNot monotonic
2023-08-24T15:32:50.792051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
8 879
 
8.5%
10 572
 
5.5%
12 550
 
5.3%
6 499
 
4.8%
7 354
 
3.4%
5 164
 
1.6%
9 130
 
1.3%
4 129
 
1.2%
14 95
 
0.9%
16 56
 
0.5%
Other values (15) 169
 
1.6%
(Missing) 6747
65.2%
ValueCountFrequency (%)
1 4
 
< 0.1%
2 22
 
0.2%
3 16
 
0.2%
4 129
 
1.2%
5 164
 
1.6%
6 499
4.8%
7 354
3.4%
8 879
8.5%
9 130
 
1.3%
10 572
5.5%
ValueCountFrequency (%)
1200 1
 
< 0.1%
800 1
 
< 0.1%
30 2
 
< 0.1%
25 6
 
0.1%
24 3
 
< 0.1%
22 3
 
< 0.1%
20 21
 
0.2%
18 19
 
0.2%
17 3
 
< 0.1%
16 56
0.5%

Number of Cabins
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct17
Distinct (%)0.3%
Missing3869
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean2.1490347
Minimum-1
Maximum96
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)< 0.1%
Memory size80.9 KiB
2023-08-24T15:32:51.161932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum96
Range97
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1450052
Coefficient of variation (CV)0.99812497
Kurtosis970.2727
Mean2.1490347
Median Absolute Deviation (MAD)1
Skewness26.599079
Sum13915
Variance4.6010475
MonotonicityNot monotonic
2023-08-24T15:32:51.516817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2 2419
23.4%
1 2100
20.3%
3 1369
 
13.2%
4 442
 
4.3%
5 98
 
0.9%
6 29
 
0.3%
8 5
 
< 0.1%
7 4
 
< 0.1%
-1 1
 
< 0.1%
43 1
 
< 0.1%
Other values (7) 7
 
0.1%
(Missing) 3869
37.4%
ValueCountFrequency (%)
-1 1
 
< 0.1%
1 2100
20.3%
2 2419
23.4%
3 1369
13.2%
4 442
 
4.3%
5 98
 
0.9%
6 29
 
0.3%
7 4
 
< 0.1%
8 5
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
96 1
 
< 0.1%
74 1
 
< 0.1%
69 1
 
< 0.1%
52 1
 
< 0.1%
43 1
 
< 0.1%
18 1
 
< 0.1%
10 1
 
< 0.1%
9 1
 
< 0.1%
8 5
< 0.1%
7 4
< 0.1%

Number of beds
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct22
Distinct (%)0.3%
Missing3937
Missing (%)38.1%
Infinite0
Infinite (%)0.0%
Mean4.3457156
Minimum-23
Maximum266
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)< 0.1%
Memory size80.9 KiB
2023-08-24T15:32:51.844712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-23
5-th percentile2
Q12
median4
Q36
95-th percentile8
Maximum266
Range289
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.9742231
Coefficient of variation (CV)0.91451522
Kurtosis2944.5981
Mean4.3457156
Median Absolute Deviation (MAD)2
Skewness45.343691
Sum27843
Variance15.794449
MonotonicityNot monotonic
2023-08-24T15:32:52.176607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
4 2391
23.1%
2 1375
 
13.3%
6 1330
 
12.9%
8 311
 
3.0%
3 241
 
2.3%
1 240
 
2.3%
5 234
 
2.3%
7 117
 
1.1%
10 66
 
0.6%
12 40
 
0.4%
Other values (12) 62
 
0.6%
(Missing) 3937
38.1%
ValueCountFrequency (%)
-23 1
 
< 0.1%
-1 2
 
< 0.1%
1 240
 
2.3%
2 1375
13.3%
3 241
 
2.3%
4 2391
23.1%
5 234
 
2.3%
6 1330
12.9%
7 117
 
1.1%
8 311
 
3.0%
ValueCountFrequency (%)
266 1
 
< 0.1%
69 1
 
< 0.1%
26 1
 
< 0.1%
18 2
 
< 0.1%
16 2
 
< 0.1%
15 5
 
< 0.1%
14 7
 
0.1%
13 3
 
< 0.1%
12 40
0.4%
11 10
 
0.1%

Hull Color
Text

MISSING 

Distinct377
Distinct (%)11.4%
Missing7033
Missing (%)68.0%
Memory size80.9 KiB
2023-08-24T15:32:52.562482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length32
Mean length8.4947146
Min length1

Characters and Unicode

Total characters28126
Distinct characters78
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique276 ?
Unique (%)8.3%

Sample

1st rowwhite
2nd rowwhite white
3rd rowgrey
4th rowred weiss
5th rowgrey grey
ValueCountFrequency (%)
white 2778
52.5%
blue 550
 
10.4%
grey 246
 
4.6%
black 188
 
3.5%
weiss 113
 
2.1%
wei㟠77
 
1.5%
witte 74
 
1.4%
romp 69
 
1.3%
red 65
 
1.2%
blau 64
 
1.2%
Other values (252) 1072
 
20.2%
2023-08-24T15:32:53.584154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4643
16.5%
i 3468
12.3%
t 3198
11.4%
h 2928
10.4%
w 2612
9.3%
1987
 
7.1%
l 1059
 
3.8%
u 828
 
2.9%
r 803
 
2.9%
b 740
 
2.6%
Other values (68) 5860
20.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24226
86.1%
Space Separator 1987
 
7.1%
Uppercase Letter 1674
 
6.0%
Control 89
 
0.3%
Other Punctuation 86
 
0.3%
Decimal Number 31
 
0.1%
Dash Punctuation 9
 
< 0.1%
Modifier Symbol 8
 
< 0.1%
Other Number 7
 
< 0.1%
Other Symbol 3
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4643
19.2%
i 3468
14.3%
t 3198
13.2%
h 2928
12.1%
w 2612
10.8%
l 1059
 
4.4%
u 828
 
3.4%
r 803
 
3.3%
b 740
 
3.1%
a 676
 
2.8%
Other values (16) 3271
13.5%
Uppercase Letter
ValueCountFrequency (%)
W 708
42.3%
B 473
28.3%
à 109
 
6.5%
G 67
 
4.0%
O 42
 
2.5%
A 40
 
2.4%
R 32
 
1.9%
C 32
 
1.9%
L 30
 
1.8%
N 29
 
1.7%
Other values (16) 112
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 15
48.4%
0 4
 
12.9%
9 4
 
12.9%
1 3
 
9.7%
3 2
 
6.5%
8 1
 
3.2%
4 1
 
3.2%
6 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
? 35
40.7%
/ 30
34.9%
, 9
 
10.5%
' 6
 
7.0%
¶ 2
 
2.3%
. 2
 
2.3%
& 2
 
2.3%
Control
ValueCountFrequency (%)
Ÿ 88
98.9%
1
 
1.1%
Other Number
ValueCountFrequency (%)
¼ 6
85.7%
¹ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1987
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
¨ 8
100.0%
Other Symbol
ValueCountFrequency (%)
© 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Currency Symbol
ValueCountFrequency (%)
¤ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25900
92.1%
Common 2226
 
7.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4643
17.9%
i 3468
13.4%
t 3198
12.3%
h 2928
11.3%
w 2612
10.1%
l 1059
 
4.1%
u 828
 
3.2%
r 803
 
3.1%
b 740
 
2.9%
W 708
 
2.7%
Other values (42) 4913
19.0%
Common
ValueCountFrequency (%)
1987
89.3%
Ÿ 88
 
4.0%
? 35
 
1.6%
/ 30
 
1.3%
2 15
 
0.7%
, 9
 
0.4%
- 9
 
0.4%
¨ 8
 
0.4%
' 6
 
0.3%
¼ 6
 
0.3%
Other values (16) 33
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27908
99.2%
None 218
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4643
16.6%
i 3468
12.4%
t 3198
11.5%
h 2928
10.5%
w 2612
9.4%
1987
 
7.1%
l 1059
 
3.8%
u 828
 
3.0%
r 803
 
2.9%
b 740
 
2.7%
Other values (60) 5642
20.2%
None
ValueCountFrequency (%)
à 109
50.0%
Ÿ 88
40.4%
¨ 8
 
3.7%
¼ 6
 
2.8%
© 3
 
1.4%
¶ 2
 
0.9%
¤ 1
 
0.5%
¹ 1
 
0.5%

Number of Toilets
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct11
Distinct (%)0.5%
Missing8188
Missing (%)79.2%
Infinite0
Infinite (%)0.0%
Mean1.7639147
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.9 KiB
2023-08-24T15:32:54.015019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum84
Range83
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.0763649
Coefficient of variation (CV)1.1771346
Kurtosis1142.7823
Mean1.7639147
Median Absolute Deviation (MAD)0
Skewness29.155502
Sum3803
Variance4.3112912
MonotonicityNot monotonic
2023-08-24T15:32:54.391895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 1209
 
11.7%
2 596
 
5.8%
3 168
 
1.6%
4 131
 
1.3%
5 34
 
0.3%
6 9
 
0.1%
7 4
 
< 0.1%
8 2
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 8188
79.2%
ValueCountFrequency (%)
1 1209
11.7%
2 596
5.8%
3 168
 
1.6%
4 131
 
1.3%
5 34
 
0.3%
6 9
 
0.1%
7 4
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
84 1
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
8 2
 
< 0.1%
7 4
 
< 0.1%
6 9
 
0.1%
5 34
 
0.3%
4 131
 
1.3%
3 168
 
1.6%
2 596
5.8%

Number of Bathrooms
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)1.1%
Missing9881
Missing (%)95.5%
Memory size80.9 KiB
1.0
361 
2.0
83 
3.0
 
10
4.0
 
7
6.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1389
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 361
 
3.5%
2.0 83
 
0.8%
3.0 10
 
0.1%
4.0 7
 
0.1%
6.0 2
 
< 0.1%
(Missing) 9881
95.5%

Length

2023-08-24T15:32:54.805765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-24T15:32:55.191637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0 361
78.0%
2.0 83
 
17.9%
3.0 10
 
2.2%
4.0 7
 
1.5%
6.0 2
 
0.4%

Most occurring characters

ValueCountFrequency (%)
. 463
33.3%
0 463
33.3%
1 361
26.0%
2 83
 
6.0%
3 10
 
0.7%
4 7
 
0.5%
6 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 926
66.7%
Other Punctuation 463
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 463
50.0%
1 361
39.0%
2 83
 
9.0%
3 10
 
1.1%
4 7
 
0.8%
6 2
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 463
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 463
33.3%
0 463
33.3%
1 361
26.0%
2 83
 
6.0%
3 10
 
0.7%
4 7
 
0.5%
6 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 463
33.3%
0 463
33.3%
1 361
26.0%
2 83
 
6.0%
3 10
 
0.7%
4 7
 
0.5%
6 2
 
0.1%

Number of Showers
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)0.5%
Missing8403
Missing (%)81.2%
Infinite0
Infinite (%)0.0%
Mean1.550747
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.9 KiB
2023-08-24T15:32:55.559520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum10
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.93009572
Coefficient of variation (CV)0.59977269
Kurtosis9.5627104
Mean1.550747
Median Absolute Deviation (MAD)0
Skewness2.4933031
Sum3010
Variance0.86507805
MonotonicityNot monotonic
2023-08-24T15:32:55.948395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 1237
 
12.0%
2 491
 
4.7%
3 105
 
1.0%
4 82
 
0.8%
5 19
 
0.2%
8 3
 
< 0.1%
6 2
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 8403
81.2%
ValueCountFrequency (%)
1 1237
12.0%
2 491
 
4.7%
3 105
 
1.0%
4 82
 
0.8%
5 19
 
0.2%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 3
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
8 3
 
< 0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 19
 
0.2%
4 82
 
0.8%
3 105
 
1.0%
2 491
 
4.7%
1 1237
12.0%

Material
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct11
Distinct (%)0.1%
Missing1832
Missing (%)17.7%
Memory size80.9 KiB
GRP
5754 
PVC
1156 
Steel
978 
Wood
 
245
Aluminium
 
237
Other values (6)
 
142

Length

Max length19
Median length3
Mean length3.5230263
Min length3

Characters and Unicode

Total characters29988
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowThermoplastic
2nd rowAluminium
3rd rowAluminium
4th rowAluminium
5th rowAluminium

Common Values

ValueCountFrequency (%)
GRP 5754
55.6%
PVC 1156
 
11.2%
Steel 978
 
9.5%
Wood 245
 
2.4%
Aluminium 237
 
2.3%
Plastic 88
 
0.9%
Carbon Fiber 32
 
0.3%
Thermoplastic 15
 
0.1%
Hypalon 5
 
< 0.1%
Reinforced concrete 1
 
< 0.1%
(Missing) 1832
 
17.7%

Length

2023-08-24T15:32:56.431242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
grp 5754
67.3%
pvc 1156
 
13.5%
steel 978
 
11.4%
wood 245
 
2.9%
aluminium 237
 
2.8%
plastic 88
 
1.0%
carbon 32
 
0.4%
fiber 32
 
0.4%
thermoplastic 15
 
0.2%
hypalon 5
 
0.1%
Other values (3) 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
P 6998
23.3%
R 5756
19.2%
G 5754
19.2%
e 2008
 
6.7%
l 1323
 
4.4%
C 1188
 
4.0%
V 1156
 
3.9%
t 1082
 
3.6%
S 978
 
3.3%
i 610
 
2.0%
Other values (20) 3135
10.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 22364
74.6%
Lowercase Letter 7591
 
25.3%
Space Separator 33
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2008
26.5%
l 1323
17.4%
t 1082
14.3%
i 610
 
8.0%
o 544
 
7.2%
m 489
 
6.4%
u 475
 
6.3%
n 276
 
3.6%
d 246
 
3.2%
a 140
 
1.8%
Other values (8) 398
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
P 6998
31.3%
R 5756
25.7%
G 5754
25.7%
C 1188
 
5.3%
V 1156
 
5.2%
S 978
 
4.4%
W 245
 
1.1%
A 237
 
1.1%
F 32
 
0.1%
T 15
 
0.1%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29955
99.9%
Common 33
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 6998
23.4%
R 5756
19.2%
G 5754
19.2%
e 2008
 
6.7%
l 1323
 
4.4%
C 1188
 
4.0%
V 1156
 
3.9%
t 1082
 
3.6%
S 978
 
3.3%
i 610
 
2.0%
Other values (19) 3102
10.4%
Common
ValueCountFrequency (%)
33
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29988
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 6998
23.3%
R 5756
19.2%
G 5754
19.2%
e 2008
 
6.7%
l 1323
 
4.4%
C 1188
 
4.0%
V 1156
 
3.9%
t 1082
 
3.6%
S 978
 
3.3%
i 610
 
2.0%
Other values (20) 3135
10.5%

Fresh Water Cap
Text

MISSING 

Distinct287
Distinct (%)13.6%
Missing8226
Missing (%)79.5%
Memory size80.9 KiB
2023-08-24T15:32:56.955074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9050992
Min length3

Characters and Unicode

Total characters10389
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)6.0%

Sample

1st row70 l
2nd row205 l
3rd row100 l
4th row40 l
5th row60 l
ValueCountFrequency (%)
l 2118
50.0%
100 122
 
2.9%
200 111
 
2.6%
400 97
 
2.3%
80 90
 
2.1%
300 78
 
1.8%
50 77
 
1.8%
250 73
 
1.7%
500 69
 
1.6%
150 62
 
1.5%
Other values (278) 1339
31.6%
2023-08-24T15:32:58.030725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2683
25.8%
2118
20.4%
l 2118
20.4%
1 646
 
6.2%
5 642
 
6.2%
2 546
 
5.3%
4 415
 
4.0%
3 359
 
3.5%
6 284
 
2.7%
8 254
 
2.4%
Other values (2) 324
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6153
59.2%
Space Separator 2118
 
20.4%
Lowercase Letter 2118
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2683
43.6%
1 646
 
10.5%
5 642
 
10.4%
2 546
 
8.9%
4 415
 
6.7%
3 359
 
5.8%
6 284
 
4.6%
8 254
 
4.1%
7 219
 
3.6%
9 105
 
1.7%
Space Separator
ValueCountFrequency (%)
2118
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 2118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8271
79.6%
Latin 2118
 
20.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2683
32.4%
2118
25.6%
1 646
 
7.8%
5 642
 
7.8%
2 546
 
6.6%
4 415
 
5.0%
3 359
 
4.3%
6 284
 
3.4%
8 254
 
3.1%
7 219
 
2.6%
Latin
ValueCountFrequency (%)
l 2118
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2683
25.8%
2118
20.4%
l 2118
20.4%
1 646
 
6.2%
5 642
 
6.2%
2 546
 
5.3%
4 415
 
4.0%
3 359
 
3.5%
6 284
 
2.7%
8 254
 
2.4%
Other values (2) 324
 
3.1%

Holding Tank
Text

MISSING 

Distinct104
Distinct (%)12.7%
Missing9525
Missing (%)92.1%
Memory size80.9 KiB
2023-08-24T15:32:58.527565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.6043956
Min length3

Characters and Unicode

Total characters3771
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)6.1%

Sample

1st row150 l
2nd row60 l
3rd row80 l
4th row40 l
5th row50 l
ValueCountFrequency (%)
l 819
50.0%
80 82
 
5.0%
100 82
 
5.0%
200 67
 
4.1%
50 61
 
3.7%
150 53
 
3.2%
120 46
 
2.8%
60 39
 
2.4%
40 39
 
2.4%
300 27
 
1.6%
Other values (95) 323
 
19.7%
2023-08-24T15:32:59.523247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 970
25.7%
819
21.7%
l 819
21.7%
1 281
 
7.5%
5 204
 
5.4%
2 202
 
5.4%
8 117
 
3.1%
4 112
 
3.0%
6 93
 
2.5%
3 73
 
1.9%
Other values (2) 81
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2133
56.6%
Space Separator 819
 
21.7%
Lowercase Letter 819
 
21.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 970
45.5%
1 281
 
13.2%
5 204
 
9.6%
2 202
 
9.5%
8 117
 
5.5%
4 112
 
5.3%
6 93
 
4.4%
3 73
 
3.4%
7 61
 
2.9%
9 20
 
0.9%
Space Separator
ValueCountFrequency (%)
819
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 819
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2952
78.3%
Latin 819
 
21.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 970
32.9%
819
27.7%
1 281
 
9.5%
5 204
 
6.9%
2 202
 
6.8%
8 117
 
4.0%
4 112
 
3.8%
6 93
 
3.2%
3 73
 
2.5%
7 61
 
2.1%
Latin
ValueCountFrequency (%)
l 819
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3771
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 970
25.7%
819
21.7%
l 819
21.7%
1 281
 
7.5%
5 204
 
5.4%
2 202
 
5.4%
8 117
 
3.1%
4 112
 
3.0%
6 93
 
2.5%
3 73
 
1.9%
Other values (2) 81
 
2.1%

Propulsion
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)0.2%
Missing7053
Missing (%)68.2%
Memory size80.9 KiB
Inboard with Shaft
1188 
Sterndrive
1184 
Outboard, four-stroke
787 
POD Drive
 
53
Outboard, two-stroke
 
40
Other values (3)
 
39

Length

Max length21
Median length20
Mean length15.628988
Min length9

Characters and Unicode

Total characters51435
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowInboard with Shaft
2nd rowOutboard, four-stroke
3rd rowOutboard, four-stroke
4th rowSterndrive
5th rowOutboard, four-stroke

Common Values

ValueCountFrequency (%)
Inboard with Shaft 1188
 
11.5%
Sterndrive 1184
 
11.4%
Outboard, four-stroke 787
 
7.6%
POD Drive 53
 
0.5%
Outboard, two-stroke 40
 
0.4%
Jet Drive 16
 
0.2%
Forward Drive 14
 
0.1%
Saildrive 9
 
0.1%
(Missing) 7053
68.2%

Length

2023-08-24T15:33:00.018090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-24T15:33:00.464946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
inboard 1188
18.1%
with 1188
18.1%
shaft 1188
18.1%
sterndrive 1184
18.0%
outboard 827
12.6%
four-stroke 787
12.0%
drive 83
 
1.3%
pod 53
 
0.8%
two-stroke 40
 
0.6%
jet 16
 
0.2%
Other values (2) 23
 
0.3%

Most occurring characters

ValueCountFrequency (%)
r 6117
 
11.9%
t 5270
 
10.2%
o 3683
 
7.2%
e 3303
 
6.4%
3286
 
6.4%
a 3226
 
6.3%
d 3222
 
6.3%
i 2473
 
4.8%
S 2381
 
4.6%
h 2376
 
4.6%
Other values (17) 16098
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41827
81.3%
Uppercase Letter 4668
 
9.1%
Space Separator 3286
 
6.4%
Other Punctuation 827
 
1.6%
Dash Punctuation 827
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 6117
14.6%
t 5270
12.6%
o 3683
8.8%
e 3303
7.9%
a 3226
7.7%
d 3222
7.7%
i 2473
 
5.9%
h 2376
 
5.7%
n 2372
 
5.7%
b 2015
 
4.8%
Other values (7) 7770
18.6%
Uppercase Letter
ValueCountFrequency (%)
S 2381
51.0%
I 1188
25.4%
O 880
 
18.9%
D 136
 
2.9%
P 53
 
1.1%
J 16
 
0.3%
F 14
 
0.3%
Space Separator
ValueCountFrequency (%)
3286
100.0%
Other Punctuation
ValueCountFrequency (%)
, 827
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 827
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 46495
90.4%
Common 4940
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 6117
13.2%
t 5270
11.3%
o 3683
 
7.9%
e 3303
 
7.1%
a 3226
 
6.9%
d 3222
 
6.9%
i 2473
 
5.3%
S 2381
 
5.1%
h 2376
 
5.1%
n 2372
 
5.1%
Other values (14) 12072
26.0%
Common
ValueCountFrequency (%)
3286
66.5%
, 827
 
16.7%
- 827
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 6117
 
11.9%
t 5270
 
10.2%
o 3683
 
7.2%
e 3303
 
6.4%
3286
 
6.4%
a 3226
 
6.3%
d 3222
 
6.3%
i 2473
 
4.8%
S 2381
 
4.6%
h 2376
 
4.6%
Other values (17) 16098
31.3%

Engine
Text

MISSING 

Distinct4752
Distinct (%)49.8%
Missing809
Missing (%)7.8%
Memory size80.9 KiB
2023-08-24T15:33:01.236698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length73
Mean length16.543471
Min length1

Characters and Unicode

Total characters157742
Distinct characters105
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3991 ?
Unique (%)41.9%

Sample

1st row (Permission for Lake of Constance)
2nd rowVolvoPenta MD 2002
3rd row (Permission for Lake of Constance)
4th rowYamaha F8 BMH 5.6 kW
5th row1 x 15 HP / 11 kW
ValueCountFrequency (%)
volvo 2899
 
9.4%
penta 2313
 
7.5%
x 918
 
3.0%
mercruiser 860
 
2.8%
mercury 689
 
2.2%
hp 686
 
2.2%
2 643
 
2.1%
permission 639
 
2.1%
for 639
 
2.1%
lake 639
 
2.1%
Other values (2928) 19760
64.4%
2023-08-24T15:33:02.590260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21724
 
13.8%
e 8285
 
5.3%
o 8265
 
5.2%
r 6781
 
4.3%
a 6608
 
4.2%
n 5543
 
3.5%
P 4878
 
3.1%
V 4611
 
2.9%
0 4447
 
2.8%
i 4036
 
2.6%
Other values (95) 82564
52.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 67607
42.9%
Uppercase Letter 44239
28.0%
Space Separator 21731
 
13.8%
Decimal Number 19890
 
12.6%
Other Punctuation 1829
 
1.2%
Dash Punctuation 936
 
0.6%
Open Punctuation 732
 
0.5%
Close Punctuation 725
 
0.5%
Control 19
 
< 0.1%
Math Symbol 14
 
< 0.1%
Other values (5) 20
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 4878
 
11.0%
V 4611
 
10.4%
M 4010
 
9.1%
A 2894
 
6.5%
C 2690
 
6.1%
D 2592
 
5.9%
L 2430
 
5.5%
E 2412
 
5.5%
T 2056
 
4.6%
O 2046
 
4.6%
Other values (18) 13620
30.8%
Lowercase Letter
ValueCountFrequency (%)
e 8285
12.3%
o 8265
12.2%
r 6781
10.0%
a 6608
9.8%
n 5543
 
8.2%
i 4036
 
6.0%
t 3794
 
5.6%
s 3625
 
5.4%
l 3526
 
5.2%
v 2623
 
3.9%
Other values (17) 14521
21.5%
Other Punctuation
ValueCountFrequency (%)
. 826
45.2%
/ 495
27.1%
, 450
24.6%
& 12
 
0.7%
; 9
 
0.5%
: 9
 
0.5%
? 8
 
0.4%
¡ 6
 
0.3%
# 3
 
0.2%
¶ 3
 
0.2%
Other values (5) 8
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 4447
22.4%
2 3162
15.9%
1 2516
12.6%
5 2014
10.1%
3 1880
9.5%
4 1784
9.0%
6 1571
 
7.9%
8 1034
 
5.2%
7 898
 
4.5%
9 584
 
2.9%
Control
ValueCountFrequency (%)
Ÿ 6
31.6%
€ 5
26.3%
“ 3
15.8%
œ 2
 
10.5%
ÂŽ 1
 
5.3%
„ 1
 
5.3%
— 1
 
5.3%
Currency Symbol
ValueCountFrequency (%)
¢ 2
33.3%
¤ 2
33.3%
$ 1
16.7%
Â¥ 1
16.7%
Math Symbol
ValueCountFrequency (%)
+ 12
85.7%
¬ 1
 
7.1%
| 1
 
7.1%
Other Symbol
ValueCountFrequency (%)
© 8
72.7%
° 2
 
18.2%
¦ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
21724
> 99.9%
  7
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 936
100.0%
Open Punctuation
ValueCountFrequency (%)
( 732
100.0%
Close Punctuation
ValueCountFrequency (%)
) 725
100.0%
Modifier Symbol
ValueCountFrequency (%)
¸ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 111846
70.9%
Common 45896
29.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8285
 
7.4%
o 8265
 
7.4%
r 6781
 
6.1%
a 6608
 
5.9%
n 5543
 
5.0%
P 4878
 
4.4%
V 4611
 
4.1%
i 4036
 
3.6%
M 4010
 
3.6%
t 3794
 
3.4%
Other values (45) 55035
49.2%
Common
ValueCountFrequency (%)
21724
47.3%
0 4447
 
9.7%
2 3162
 
6.9%
1 2516
 
5.5%
5 2014
 
4.4%
3 1880
 
4.1%
4 1784
 
3.9%
6 1571
 
3.4%
8 1034
 
2.3%
- 936
 
2.0%
Other values (40) 4828
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 157635
99.9%
None 107
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21724
 
13.8%
e 8285
 
5.3%
o 8265
 
5.2%
r 6781
 
4.3%
a 6608
 
4.2%
n 5543
 
3.5%
P 4878
 
3.1%
V 4611
 
2.9%
0 4447
 
2.8%
i 4036
 
2.6%
Other values (72) 82457
52.3%
None
ValueCountFrequency (%)
à 37
34.6%
 12
 
11.2%
© 8
 
7.5%
  7
 
6.5%
¡ 6
 
5.6%
Ÿ 6
 
5.6%
€ 5
 
4.7%
â 3
 
2.8%
“ 3
 
2.8%
¶ 3
 
2.8%
Other values (13) 17
15.9%

Engine Performance
Text

MISSING 

Distinct843
Distinct (%)10.5%
Missing2281
Missing (%)22.1%
Memory size80.9 KiB
2023-08-24T15:33:03.242050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length18.861094
Min length16

Characters and Unicode

Total characters152077
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique406 ?
Unique (%)5.0%

Sample

1st row1 x 18 HP / 13 kW
2nd row1 x 15 HP / 11 kW
3rd row1 x 2 HP / 1.5 kW
4th row1 x 130 HP / 96 kW
5th row1 x 1 HP / 0.7 kW
ValueCountFrequency (%)
kw 8063
14.3%
x 8063
14.3%
hp 8063
14.3%
8063
14.3%
2 4299
 
7.6%
1 3860
 
6.8%
221 505
 
0.9%
300 504
 
0.9%
147 471
 
0.8%
200 470
 
0.8%
Other values (879) 14080
24.9%
2023-08-24T15:33:04.481656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48378
31.8%
1 11773
 
7.7%
2 11539
 
7.6%
0 9273
 
6.1%
x 8063
 
5.3%
H 8063
 
5.3%
P 8063
 
5.3%
/ 8063
 
5.3%
k 8063
 
5.3%
W 8063
 
5.3%
Other values (8) 22736
15.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55123
36.2%
Space Separator 48378
31.8%
Uppercase Letter 24189
15.9%
Lowercase Letter 16126
 
10.6%
Other Punctuation 8261
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11773
21.4%
2 11539
20.9%
0 9273
16.8%
5 5089
9.2%
3 4331
 
7.9%
4 3440
 
6.2%
7 2983
 
5.4%
6 2376
 
4.3%
8 2363
 
4.3%
9 1956
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
H 8063
33.3%
P 8063
33.3%
W 8063
33.3%
Lowercase Letter
ValueCountFrequency (%)
x 8063
50.0%
k 8063
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 8063
97.6%
. 198
 
2.4%
Space Separator
ValueCountFrequency (%)
48378
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 111762
73.5%
Latin 40315
 
26.5%

Most frequent character per script

Common
ValueCountFrequency (%)
48378
43.3%
1 11773
 
10.5%
2 11539
 
10.3%
0 9273
 
8.3%
/ 8063
 
7.2%
5 5089
 
4.6%
3 4331
 
3.9%
4 3440
 
3.1%
7 2983
 
2.7%
6 2376
 
2.1%
Other values (3) 4517
 
4.0%
Latin
ValueCountFrequency (%)
x 8063
20.0%
H 8063
20.0%
P 8063
20.0%
k 8063
20.0%
W 8063
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48378
31.8%
1 11773
 
7.7%
2 11539
 
7.6%
0 9273
 
6.1%
x 8063
 
5.3%
H 8063
 
5.3%
P 8063
 
5.3%
/ 8063
 
5.3%
k 8063
 
5.3%
W 8063
 
5.3%
Other values (8) 22736
15.0%

Fuel Capacity
Text

MISSING 

Distinct716
Distinct (%)10.5%
Missing3530
Missing (%)34.1%
Memory size80.9 KiB
2023-08-24T15:33:05.212418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.2785442
Min length3

Characters and Unicode

Total characters35968
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)4.5%

Sample

1st row50 l
2nd row40 l
3rd row80 l
4th row20 l
5th row25 l
ValueCountFrequency (%)
l 6814
50.0%
400 231
 
1.7%
1000 215
 
1.6%
800 194
 
1.4%
200 191
 
1.4%
500 180
 
1.3%
600 163
 
1.2%
300 157
 
1.2%
1200 143
 
1.0%
2000 132
 
1.0%
Other values (707) 5208
38.2%
2023-08-24T15:33:06.435026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9828
27.3%
6814
18.9%
l 6814
18.9%
1 2586
 
7.2%
2 2330
 
6.5%
5 1953
 
5.4%
3 1189
 
3.3%
4 1133
 
3.2%
8 964
 
2.7%
6 944
 
2.6%
Other values (2) 1413
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22340
62.1%
Space Separator 6814
 
18.9%
Lowercase Letter 6814
 
18.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9828
44.0%
1 2586
 
11.6%
2 2330
 
10.4%
5 1953
 
8.7%
3 1189
 
5.3%
4 1133
 
5.1%
8 964
 
4.3%
6 944
 
4.2%
7 808
 
3.6%
9 605
 
2.7%
Space Separator
ValueCountFrequency (%)
6814
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 6814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29154
81.1%
Latin 6814
 
18.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9828
33.7%
6814
23.4%
1 2586
 
8.9%
2 2330
 
8.0%
5 1953
 
6.7%
3 1189
 
4.1%
4 1133
 
3.9%
8 964
 
3.3%
6 944
 
3.2%
7 808
 
2.8%
Latin
ValueCountFrequency (%)
l 6814
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9828
27.3%
6814
18.9%
l 6814
18.9%
1 2586
 
7.2%
2 2330
 
6.5%
5 1953
 
5.4%
3 1189
 
3.3%
4 1133
 
3.2%
8 964
 
2.7%
6 944
 
2.6%
Other values (2) 1413
 
3.9%

Fuel Type
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct6
Distinct (%)0.1%
Missing2322
Missing (%)22.4%
Memory size80.9 KiB
Diesel
4748 
Unleaded
3199 
Electric
 
56
Gas
 
16
Hybrid
 
2

Length

Max length8
Median length6
Mean length6.8056594
Min length3

Characters and Unicode

Total characters54595
Distinct characters20
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowUnleaded
2nd rowUnleaded
3rd rowElectric
4th rowUnleaded
5th rowUnleaded

Common Values

ValueCountFrequency (%)
Diesel 4748
45.9%
Unleaded 3199
30.9%
Electric 56
 
0.5%
Gas 16
 
0.2%
Hybrid 2
 
< 0.1%
Propane 1
 
< 0.1%
(Missing) 2322
22.4%

Length

2023-08-24T15:33:07.004840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-24T15:33:07.392716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
diesel 4748
59.2%
unleaded 3199
39.9%
electric 56
 
0.7%
gas 16
 
0.2%
hybrid 2
 
< 0.1%
propane 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 15951
29.2%
l 8003
14.7%
d 6400
11.7%
i 4806
 
8.8%
s 4764
 
8.7%
D 4748
 
8.7%
a 3216
 
5.9%
n 3200
 
5.9%
U 3199
 
5.9%
c 112
 
0.2%
Other values (10) 196
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46573
85.3%
Uppercase Letter 8022
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15951
34.2%
l 8003
17.2%
d 6400
13.7%
i 4806
 
10.3%
s 4764
 
10.2%
a 3216
 
6.9%
n 3200
 
6.9%
c 112
 
0.2%
r 59
 
0.1%
t 56
 
0.1%
Other values (4) 6
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
D 4748
59.2%
U 3199
39.9%
E 56
 
0.7%
G 16
 
0.2%
H 2
 
< 0.1%
P 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 54595
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15951
29.2%
l 8003
14.7%
d 6400
11.7%
i 4806
 
8.8%
s 4764
 
8.7%
D 4748
 
8.7%
a 3216
 
5.9%
n 3200
 
5.9%
U 3199
 
5.9%
c 112
 
0.2%
Other values (10) 196
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54595
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 15951
29.2%
l 8003
14.7%
d 6400
11.7%
i 4806
 
8.8%
s 4764
 
8.7%
D 4748
 
8.7%
a 3216
 
5.9%
n 3200
 
5.9%
U 3199
 
5.9%
c 112
 
0.2%
Other values (10) 196
 
0.4%

Engine Hours
Text

MISSING 

Distinct996
Distinct (%)19.4%
Missing5211
Missing (%)50.4%
Memory size80.9 KiB
2023-08-24T15:33:07.997522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1250731
Min length3

Characters and Unicode

Total characters26307
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique561 ?
Unique (%)10.9%

Sample

1st row500 h
2nd row10 h
3rd row2850 h
4th row9 h
5th row20 h
ValueCountFrequency (%)
h 5133
50.0%
500 112
 
1.1%
700 101
 
1.0%
600 98
 
1.0%
650 88
 
0.9%
800 88
 
0.9%
300 87
 
0.8%
900 85
 
0.8%
400 75
 
0.7%
350 72
 
0.7%
Other values (987) 4327
42.1%
2023-08-24T15:33:09.049184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5614
21.3%
5133
19.5%
h 5133
19.5%
5 1937
 
7.4%
1 1874
 
7.1%
2 1232
 
4.7%
3 1129
 
4.3%
4 976
 
3.7%
8 887
 
3.4%
6 879
 
3.3%
Other values (2) 1513
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16041
61.0%
Space Separator 5133
 
19.5%
Lowercase Letter 5133
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5614
35.0%
5 1937
 
12.1%
1 1874
 
11.7%
2 1232
 
7.7%
3 1129
 
7.0%
4 976
 
6.1%
8 887
 
5.5%
6 879
 
5.5%
7 776
 
4.8%
9 737
 
4.6%
Space Separator
ValueCountFrequency (%)
5133
100.0%
Lowercase Letter
ValueCountFrequency (%)
h 5133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21174
80.5%
Latin 5133
 
19.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5614
26.5%
5133
24.2%
5 1937
 
9.1%
1 1874
 
8.9%
2 1232
 
5.8%
3 1129
 
5.3%
4 976
 
4.6%
8 887
 
4.2%
6 879
 
4.2%
7 776
 
3.7%
Latin
ValueCountFrequency (%)
h 5133
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5614
21.3%
5133
19.5%
h 5133
19.5%
5 1937
 
7.4%
1 1874
 
7.1%
2 1232
 
4.7%
3 1129
 
4.3%
4 976
 
3.7%
8 887
 
3.4%
6 879
 
3.3%
Other values (2) 1513
 
5.8%

Max Speed
Text

MISSING 

Distinct99
Distinct (%)11.1%
Missing9452
Missing (%)91.4%
Memory size80.9 KiB
2023-08-24T15:33:09.509036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8710762
Min length6

Characters and Unicode

Total characters7021
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)4.1%

Sample

1st row40 mph
2nd row25 knots
3rd row24 knots
4th row7 knots
5th row95 km/h
ValueCountFrequency (%)
knots 812
45.5%
30 116
 
6.5%
32 97
 
5.4%
km/h 73
 
4.1%
33 61
 
3.4%
35 50
 
2.8%
34 48
 
2.7%
38 34
 
1.9%
31 34
 
1.9%
28 32
 
1.8%
Other values (67) 427
23.9%
2023-08-24T15:33:10.318775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
892
12.7%
k 885
12.6%
n 812
11.6%
o 812
11.6%
t 812
11.6%
s 812
11.6%
3 558
7.9%
2 297
 
4.2%
0 203
 
2.9%
4 160
 
2.3%
Other values (10) 778
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4300
61.2%
Decimal Number 1756
25.0%
Space Separator 892
 
12.7%
Other Punctuation 73
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 558
31.8%
2 297
16.9%
0 203
 
11.6%
4 160
 
9.1%
5 134
 
7.6%
1 123
 
7.0%
8 100
 
5.7%
6 70
 
4.0%
7 61
 
3.5%
9 50
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
k 885
20.6%
n 812
18.9%
o 812
18.9%
t 812
18.9%
s 812
18.9%
m 80
 
1.9%
h 80
 
1.9%
p 7
 
0.2%
Space Separator
ValueCountFrequency (%)
892
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4300
61.2%
Common 2721
38.8%

Most frequent character per script

Common
ValueCountFrequency (%)
892
32.8%
3 558
20.5%
2 297
 
10.9%
0 203
 
7.5%
4 160
 
5.9%
5 134
 
4.9%
1 123
 
4.5%
8 100
 
3.7%
/ 73
 
2.7%
6 70
 
2.6%
Other values (2) 111
 
4.1%
Latin
ValueCountFrequency (%)
k 885
20.6%
n 812
18.9%
o 812
18.9%
t 812
18.9%
s 812
18.9%
m 80
 
1.9%
h 80
 
1.9%
p 7
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
892
12.7%
k 885
12.6%
n 812
11.6%
o 812
11.6%
t 812
11.6%
s 812
11.6%
3 558
7.9%
2 297
 
4.2%
0 203
 
2.9%
4 160
 
2.3%
Other values (10) 778
11.1%

Cruising Speed
Text

MISSING 

Distinct57
Distinct (%)10.4%
Missing9797
Missing (%)94.7%
Memory size80.9 KiB
2023-08-24T15:33:10.634674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8446069
Min length6

Characters and Unicode

Total characters4291
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)4.0%

Sample

1st row12 knots
2nd row18 knots
3rd row18 knots
4th row5 knots
5th row6 km/h
ValueCountFrequency (%)
knots 518
47.3%
25 71
 
6.5%
24 54
 
4.9%
22 51
 
4.7%
26 40
 
3.7%
23 36
 
3.3%
28 32
 
2.9%
km/h 25
 
2.3%
30 25
 
2.3%
18 20
 
1.8%
Other values (35) 222
20.3%
2023-08-24T15:33:11.370438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
547
12.7%
k 543
12.7%
n 518
12.1%
o 518
12.1%
t 518
12.1%
s 518
12.1%
2 415
9.7%
5 104
 
2.4%
1 101
 
2.4%
3 97
 
2.3%
Other values (10) 412
9.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2677
62.4%
Decimal Number 1042
 
24.3%
Space Separator 547
 
12.7%
Other Punctuation 25
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 415
39.8%
5 104
 
10.0%
1 101
 
9.7%
3 97
 
9.3%
4 70
 
6.7%
6 69
 
6.6%
8 69
 
6.6%
0 61
 
5.9%
7 40
 
3.8%
9 16
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
k 543
20.3%
n 518
19.4%
o 518
19.4%
t 518
19.4%
s 518
19.4%
m 29
 
1.1%
h 29
 
1.1%
p 4
 
0.1%
Space Separator
ValueCountFrequency (%)
547
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2677
62.4%
Common 1614
37.6%

Most frequent character per script

Common
ValueCountFrequency (%)
547
33.9%
2 415
25.7%
5 104
 
6.4%
1 101
 
6.3%
3 97
 
6.0%
4 70
 
4.3%
6 69
 
4.3%
8 69
 
4.3%
0 61
 
3.8%
7 40
 
2.5%
Other values (2) 41
 
2.5%
Latin
ValueCountFrequency (%)
k 543
20.3%
n 518
19.4%
o 518
19.4%
t 518
19.4%
s 518
19.4%
m 29
 
1.1%
h 29
 
1.1%
p 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
547
12.7%
k 543
12.7%
n 518
12.1%
o 518
12.1%
t 518
12.1%
s 518
12.1%
2 415
9.7%
5 104
 
2.4%
1 101
 
2.4%
3 97
 
2.3%
Other values (10) 412
9.6%
Distinct3177
Distinct (%)30.8%
Missing43
Missing (%)0.4%
Memory size80.9 KiB
2023-08-24T15:33:11.852283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length65
Mean length29.342006
Min length2

Characters and Unicode

Total characters302252
Distinct characters118
Distinct categories18 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2126 ?
Unique (%)20.6%

Sample

1st rowSwitzerland » Lake Geneva » Vésenaz
2nd rowGermany » Bönningstedt
3rd rowSwitzerland » Lake of Zurich » Stäfa ZH
4th rowDenmark » Svendborg
5th rowNordsee » Västra Frölunda
ValueCountFrequency (%)
â» 12700
27.2%
germany 1998
 
4.3%
france 1901
 
4.1%
italy 1875
 
4.0%
switzerland 1175
 
2.5%
netherlands 1099
 
2.4%
croatia 864
 
1.9%
hrvatska 828
 
1.8%
spain 725
 
1.6%
lake 580
 
1.2%
Other values (2473) 22957
49.2%
2023-08-24T15:33:12.853961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37350
 
12.4%
a 27062
 
9.0%
e 23344
 
7.7%
n 18330
 
6.1%
r 17962
 
5.9%
 12711
 
4.2%
» 12700
 
4.2%
i 12204
 
4.0%
t 12044
 
4.0%
l 10335
 
3.4%
Other values (108) 118210
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 184326
61.0%
Uppercase Letter 59960
 
19.8%
Space Separator 37351
 
12.4%
Final Punctuation 12700
 
4.2%
Other Punctuation 2586
 
0.9%
Decimal Number 1145
 
0.4%
Open Punctuation 1137
 
0.4%
Close Punctuation 1137
 
0.4%
Dash Punctuation 1032
 
0.3%
Currency Symbol 305
 
0.1%
Other values (8) 573
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
 12711
21.2%
S 4164
 
6.9%
I 3720
 
6.2%
G 3565
 
5.9%
N 3238
 
5.4%
L 3101
 
5.2%
F 2773
 
4.6%
A 2664
 
4.4%
C 2552
 
4.3%
E 2396
 
4.0%
Other values (19) 19076
31.8%
Lowercase Letter
ValueCountFrequency (%)
a 27062
14.7%
e 23344
12.7%
n 18330
9.9%
r 17962
9.7%
i 12204
 
6.6%
t 12044
 
6.5%
l 10335
 
5.6%
o 8992
 
4.9%
s 6928
 
3.8%
d 6355
 
3.4%
Other values (17) 40770
22.1%
Control
ValueCountFrequency (%)
œ 19
27.5%
– 13
18.8%
Ÿ 13
18.8%
˜ 6
 
8.7%
5
 
7.2%
‰ 4
 
5.8%
„ 2
 
2.9%
Â… 2
 
2.9%
€ 1
 
1.4%
† 1
 
1.4%
Other values (3) 3
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 1745
67.5%
/ 377
 
14.6%
¶ 148
 
5.7%
. 116
 
4.5%
' 97
 
3.8%
? 55
 
2.1%
& 21
 
0.8%
" 16
 
0.6%
¡ 6
 
0.2%
; 2
 
0.1%
Other values (2) 3
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 212
18.5%
2 192
16.8%
1 155
13.5%
4 117
10.2%
3 106
9.3%
8 90
7.9%
5 84
 
7.3%
6 67
 
5.9%
7 63
 
5.5%
9 59
 
5.2%
Modifier Symbol
ValueCountFrequency (%)
´ 64
56.6%
¨ 38
33.6%
¸ 8
 
7.1%
¯ 2
 
1.8%
` 1
 
0.9%
Currency Symbol
ValueCountFrequency (%)
¤ 262
85.9%
¢ 30
 
9.8%
£ 7
 
2.3%
Â¥ 6
 
2.0%
Other Number
ValueCountFrequency (%)
¼ 256
90.1%
³ 27
 
9.5%
² 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
+ 5
62.5%
| 2
 
25.0%
± 1
 
12.5%
Space Separator
ValueCountFrequency (%)
37350
> 99.9%
  1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
© 44
60.3%
¦ 29
39.7%
Other Letter
ValueCountFrequency (%)
ª 7
70.0%
º 3
30.0%
Final Punctuation
ValueCountFrequency (%)
» 12700
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1137
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1032
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 15
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 244296
80.8%
Common 57956
 
19.2%

Most frequent character per script

Common
ValueCountFrequency (%)
37350
64.4%
» 12700
 
21.9%
, 1745
 
3.0%
( 1137
 
2.0%
) 1137
 
2.0%
- 1032
 
1.8%
/ 377
 
0.7%
¤ 262
 
0.5%
¼ 256
 
0.4%
0 212
 
0.4%
Other values (50) 1748
 
3.0%
Latin
ValueCountFrequency (%)
a 27062
 
11.1%
e 23344
 
9.6%
n 18330
 
7.5%
r 17962
 
7.4%
 12711
 
5.2%
i 12204
 
5.0%
t 12044
 
4.9%
l 10335
 
4.2%
o 8992
 
3.7%
s 6928
 
2.8%
Other values (48) 94384
38.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 274815
90.9%
None 27437
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37350
 
13.6%
a 27062
 
9.8%
e 23344
 
8.5%
n 18330
 
6.7%
r 17962
 
6.5%
i 12204
 
4.4%
t 12044
 
4.4%
l 10335
 
3.8%
o 8992
 
3.3%
s 6928
 
2.5%
Other values (71) 100264
36.5%
None
ValueCountFrequency (%)
 12711
46.3%
» 12700
46.3%
à 1004
 
3.7%
¤ 262
 
1.0%
¼ 256
 
0.9%
¶ 148
 
0.5%
´ 64
 
0.2%
© 44
 
0.2%
¨ 38
 
0.1%
¢ 30
 
0.1%
Other values (27) 180
 
0.7%

Advertisement Date
Date

MISSING 

Distinct101
Distinct (%)11.6%
Missing9474
Missing (%)91.6%
Memory size80.9 KiB
Minimum2020-01-04 00:00:00
Maximum2020-12-07 00:00:00
2023-08-24T15:33:13.269827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:33:13.691692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct680
Distinct (%)6.8%
Missing363
Missing (%)3.5%
Memory size80.9 KiB
2023-08-24T15:33:14.373473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.5598637
Min length2

Characters and Unicode

Total characters25550
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique199 ?
Unique (%)2.0%

Sample

1st row226
2nd row75
3rd row124
4th row64
5th row131
ValueCountFrequency (%)
68 91
 
0.9%
74 88
 
0.9%
67 86
 
0.9%
62 85
 
0.9%
81 85
 
0.9%
73 84
 
0.8%
69 83
 
0.8%
76 81
 
0.8%
54 81
 
0.8%
75 80
 
0.8%
Other values (670) 9137
91.5%
2023-08-24T15:33:15.439130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5394
21.1%
2 2864
11.2%
3 2343
9.2%
4 2310
9.0%
6 2265
8.9%
5 2204
8.6%
7 2190
8.6%
8 2064
 
8.1%
9 1936
 
7.6%
0 1934
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25504
99.8%
Other Punctuation 46
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5394
21.1%
2 2864
11.2%
3 2343
9.2%
4 2310
9.1%
6 2265
8.9%
5 2204
8.6%
7 2190
8.6%
8 2064
 
8.1%
9 1936
 
7.6%
0 1934
 
7.6%
Other Punctuation
ValueCountFrequency (%)
' 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25550
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5394
21.1%
2 2864
11.2%
3 2343
9.2%
4 2310
9.0%
6 2265
8.9%
5 2204
8.6%
7 2190
8.6%
8 2064
 
8.1%
9 1936
 
7.6%
0 1934
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5394
21.1%
2 2864
11.2%
3 2343
9.2%
4 2310
9.0%
6 2265
8.9%
5 2204
8.6%
7 2190
8.6%
8 2064
 
8.1%
9 1936
 
7.6%
0 1934
 
7.6%

Comments
Text

MISSING 

Distinct6631
Distinct (%)93.7%
Missing3266
Missing (%)31.6%
Memory size80.9 KiB
2023-08-24T15:33:16.295855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32759
Median length3073
Mean length1777.0006
Min length1

Characters and Unicode

Total characters12577610
Distinct characters158
Distinct categories19 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6501 ?
Unique (%)91.8%

Sample

1st rowIn den Farben weiß oder grün lieferbar.,,2 abschließbare Staufächer, 3 Sitzbänke, Spiegelplatte, Scheuerleiste, Selbstlenzventil. Wie Terhi 400 zusätzlich Seitensteuerkonsole mit mech. Steuerung (ohne Riemen, Dollen Dollenhalterungen).,,Zusätzliche Ausstattung:,,Das stabile und sichere Terhi 400 C ist mit einem Steuerstand ausgestattet und als Sport- und Freizeitboot für ein bis vier Personen auf Seen oder geschützten Meeresgebieten geeignet. Gleichzeitig ist das Boot ein guter Begleiter für Sportangler. Das Boot hat beste Fahreigenschaften über die komplette Geschwindigkeitsskala selbst mit einem kleinen Motor. Zudem ist es einfach zu slippen und zu trailern. Abschließbare Backskisten im Bug und Heck bieten darüber hinaus praktischen Stauraum. Sie können das Boot für Ihren Verwendungszweck mit Zubehör individualisieren, zum Beispiel mit einer Windschutzscheibe für den Steuerstand und Relingsätzen oder mit einer gepolsterten Liegefläche für den Bugbereich.,,Preis ab Werk zzgl. Vorfracht,,Gerne erstellen wir Ihnen ein persönliches Angebot und freuen uns auf,Ihre Kontaktaufnahme.,,Bilder können Sonderoptionen zeigen. Irrtum vorbehalten.,,,,www.gruendl.de
2nd rowMORSOM OG LETKØRT KVALITETSBÅD!,Nye Pioner 10 Classic er en snerten og sikker båd som er let at håndtere og manøvrere ? og som passer perfekt for barn og voksne.,,Den moderne model er selvdrenerende, solid, letplanende og fin at ro. Pioner 10 Classic føles vældig tryg og er samtidig egnet til mange forskellige brugsområder, nogle både store og små vil sætte pris på. Båden har plads til tre personer og er godkendt for 9.9 Hk.,,,,,,,Farver:,,Leif Larsens Special Edition version med lav konsol, ræling agter, badestige, Yamaha F9.9 Vmax Sport m. el-start og fjernbetjening, sejlklar tilbud Kr. 54.500,-!
3rd rowCrazy One´s elegante og spændende design kombinerer facinerende "motorcykel-egenskaber" med et dybt og tørt cockpit til 2 personer.,,Linieføring og udformning under vandlinien går Crazy One sjov og let at sejle, giver udfordring og spænding til race, vandski, fiskeri og som ledsagerfartøj - Den ideelle fritidsbåd for hele familien.,,Den lave vægt sikrer et sparsomt brændstofsforbrug og let håndtering på biltag, påhængsvogn, bådtrailer eller bag på en større motorbåd. Båden er udstyret med 15 hk 4-takts motor årgang 2010, sejlet minimalt af timer.
4th rowCaratteristiche tecniche,,Materiale: Polietilene Rotazionale,Motorizzazione: Gambo lungo,Lunghezza: 4,35 mt.,Larghezza: 1,73 mt.,Altezza: 0,81 mt.,Altezza specchio di poppa: 0,52 mt.,Peso: 184 kg.,Capacità (persone): CE Cat. D 12 pers. - Cat. C 8 pers,Peso massimo: CE Cat. D 910 kg. - Cat C 690 kg. (compreso motore),Potenza massima: 30 CV (22 kw),Colorazioni: Blu, Arancione, Rosso, Grigio, Nero, Giallo e Bianco,,Le imbarcazioni Whaly sono realizzate interamente con doppia parete plastica (PE) in unico pezzo e prodotte mediante la tecnica dello stampaggio rotazionale.,La progettazione, il metodo di produzione e la plastica polietilene di elevata qualità costituiscono le basi per imbarcazioni ultraresistenti, inaffondabili, indistruttibili e con necessità di manutenzione minima, caratterizzate da grande spazio interno, sicurezza e stabilità.,,Tutti i modelli Whaly 210, 270, 310, 370, 435, 440 Classic e 500 si prestano ottimamente al settore ricreativo, mentre i modelli 310, 370, 435 e 500 sono multifunzionali e sono perfetti a fini professionali. Nei modelli Whaly ad uso professionale sono fondamentalii requisiti, spesso estremi, posti dal cliente: una scuola di vela, ad esempio, desidera un’imbarcazione guida stabile, sicura e resistente e nell’ambito della navigazione professionale le imbarcazioni Whaly sono utilizzate come mezzi di salvataggio a bordo, con certificazione 94/25/EG, 2003/44/EG e NEN-EN 1914 (opzionale).,,Nei modelli ad uso ricreativo, l’accento sempre posto sulla navigazione sicura e stabile, ma un occhio riservato anche allo styling, alla comodità d’uso e al comfort senza tralasciare sicurezza, affidabilità e durata.,,Grazie a simili caratteristiche, le imbarcazioni Whaly trovano diversi campi d’applicazione:,,Navigazione da diporto,Imbarcazione da lavoro,Natante di salvataggio,Pesca sportiva,Noleggio,Scuole nautiche,,Accessori optional: Consolle, panca con gavone, remi, rollbar, tendalino, cuscineria e telo copertura totale.
5th rowDecriptino:,Small open console boat with windshield, suntanning space in bow, driver´s seat. Storage locker bow, anchor storage, front console seat with backrest cushion.,Accessories/Equipment:,Upholstery – reling bow, clamps and cleats in stainless steel, reling stern seat,Possibility in package with HONDA 40CV 4stroke (year 2004) at,€ 5.500,00,Motorisation: without engine,Condition: only lake – hull very good condition,,Visible: Gardalake,,Price:,*plus commission.
ValueCountFrequency (%)
31943
 
1.9%
and 26211
 
1.6%
the 24287
 
1.4%
in 22726
 
1.4%
de 22046
 
1.3%
with 19060
 
1.1%
a 16333
 
1.0%
und 11811
 
0.7%
of 11436
 
0.7%
to 11290
 
0.7%
Other values (158549) 1484371
88.3%
2023-08-24T15:33:17.723396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1679035
 
13.3%
e 1177054
 
9.4%
a 773406
 
6.1%
i 728141
 
5.8%
n 719476
 
5.7%
t 694916
 
5.5%
r 682383
 
5.4%
o 592927
 
4.7%
s 522491
 
4.2%
l 434076
 
3.5%
Other values (148) 4573705
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8953212
71.2%
Space Separator 1693405
 
13.5%
Uppercase Letter 976738
 
7.8%
Other Punctuation 490330
 
3.9%
Decimal Number 274086
 
2.2%
Dash Punctuation 62545
 
0.5%
Other Symbol 23889
 
0.2%
Other Number 21301
 
0.2%
Open Punctuation 15496
 
0.1%
Close Punctuation 15483
 
0.1%
Other values (9) 51125
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 89728
 
9.2%
à 84060
 
8.6%
E 64258
 
6.6%
A 64138
 
6.6%
T 58961
 
6.0%
C 53686
 
5.5%
D 44907
 
4.6%
B 44844
 
4.6%
P 41462
 
4.2%
R 41288
 
4.2%
Other values (20) 389406
39.9%
Lowercase Letter
ValueCountFrequency (%)
e 1177054
13.1%
a 773406
 
8.6%
i 728141
 
8.1%
n 719476
 
8.0%
t 694916
 
7.8%
r 682383
 
7.6%
o 592927
 
6.6%
s 522491
 
5.8%
l 434076
 
4.8%
c 345291
 
3.9%
Other values (19) 2283051
25.5%
Control
ValueCountFrequency (%)
€ 4334
29.9%
Ÿ 3607
24.9%
2878
19.9%
– 771
 
5.3%
œ 708
 
4.9%
“ 601
 
4.2%
„ 435
 
3.0%
™ 274
 
1.9%
‚ 261
 
1.8%
‰ 234
 
1.6%
Other values (16) 371
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 283644
57.8%
. 82548
 
16.8%
: 47561
 
9.7%
/ 16027
 
3.3%
? 9695
 
2.0%
\ 8464
 
1.7%
# 7719
 
1.6%
' 7199
 
1.5%
& 4930
 
1.0%
" 4688
 
1.0%
Other values (10) 17855
 
3.6%
Decimal Number
ValueCountFrequency (%)
0 67244
24.5%
2 56017
20.4%
1 43286
15.8%
3 20060
 
7.3%
5 20010
 
7.3%
4 19093
 
7.0%
6 14129
 
5.2%
8 12490
 
4.6%
9 11258
 
4.1%
7 10499
 
3.8%
Math Symbol
ValueCountFrequency (%)
+ 5002
42.8%
> 4637
39.7%
± 1416
 
12.1%
¬ 278
 
2.4%
= 219
 
1.9%
| 114
 
1.0%
~ 14
 
0.1%
< 12
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
¨ 5186
83.6%
¸ 568
 
9.2%
´ 395
 
6.4%
` 40
 
0.6%
¯ 9
 
0.1%
^ 2
 
< 0.1%
Other Number
ValueCountFrequency (%)
¼ 15274
71.7%
³ 5214
 
24.5%
² 628
 
2.9%
¹ 177
 
0.8%
½ 8
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
¤ 10635
69.6%
¢ 3311
 
21.7%
Â¥ 1152
 
7.5%
£ 168
 
1.1%
$ 4
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
© 22634
94.7%
¦ 706
 
3.0%
° 382
 
1.6%
® 167
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 15474
99.9%
[ 20
 
0.1%
{ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 15461
99.9%
] 19
 
0.1%
} 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1679035
99.2%
  14370
 
0.8%
Other Letter
ValueCountFrequency (%)
ª 850
58.9%
º 593
41.1%
Dash Punctuation
ValueCountFrequency (%)
- 62545
100.0%
Format
ValueCountFrequency (%)
­ 1143
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 623
100.0%
Final Punctuation
ValueCountFrequency (%)
» 151
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9931391
79.0%
Common 2646219
 
21.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1679035
63.5%
, 283644
 
10.7%
. 82548
 
3.1%
0 67244
 
2.5%
- 62545
 
2.4%
2 56017
 
2.1%
: 47561
 
1.8%
1 43286
 
1.6%
© 22634
 
0.9%
3 20060
 
0.8%
Other values (88) 281645
 
10.6%
Latin
ValueCountFrequency (%)
e 1177054
 
11.9%
a 773406
 
7.8%
i 728141
 
7.3%
n 719476
 
7.2%
t 694916
 
7.0%
r 682383
 
6.9%
o 592927
 
6.0%
s 522491
 
5.3%
l 434076
 
4.4%
c 345291
 
3.5%
Other values (50) 3261230
32.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12372615
98.4%
None 204995
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1679035
 
13.6%
e 1177054
 
9.5%
a 773406
 
6.3%
i 728141
 
5.9%
n 719476
 
5.8%
t 694916
 
5.6%
r 682383
 
5.5%
o 592927
 
4.8%
s 522491
 
4.2%
l 434076
 
3.5%
Other values (86) 4368710
35.3%
None
ValueCountFrequency (%)
à 84060
41.0%
© 22634
 
11.0%
¼ 15274
 
7.5%
  14370
 
7.0%
 11573
 
5.6%
¤ 10635
 
5.2%
³ 5214
 
2.5%
¨ 5186
 
2.5%
â 4571
 
2.2%
¶ 4449
 
2.2%
Other values (52) 27029
 
13.2%

Additional Comments
Text

MISSING 

Distinct2410
Distinct (%)98.2%
Missing7890
Missing (%)76.3%
Memory size80.9 KiB
2023-08-24T15:33:18.373187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2004
Median length1137
Mean length628.66707
Min length4

Characters and Unicode

Total characters1542749
Distinct characters124
Distinct categories18 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2392 ?
Unique (%)97.5%

Sample

1st rowPossibility to arrange it with a complete luxury kit (bench box with upholstery, side console, front balconies),,Price on request
2nd rowThe lightweight and sleek rowing boat for 4 people is very easy to clean and suitable for the drying area. It can be equipped with an outboard motor to 15 hp. (Examination free to 8 hp).,As an option, there are a lot of accessories like bathing ladder, sun shade, floor mats, different sizes of seat rowing and more.,You can find more 20 different boat models in the permanent boat show of Bootbau Huber AG, Stäfa. www.boot-bau.ch
3rd rowFor engines up to Type 8, the environmentally friendly boat is made of high quality, corrosion resistant,Aluminum made, as it is also used for aircraft construction,becomes. Sportsman 355 comes with aluminum rudders. The boat is from Det Norske,Veritas and has a Securmark anti-theft tag *.,SPORTSMAN 355 A gliding boat type for inland lakes and rivers.
4th rowA light rowing boat with rib profile for inland lakes. Can be used with smaller outboard motors or electric motors up to max. Equip 2.5 hp.,,FISHING 410 comes with aluminum rudders and rescue ladder.,,The environmentally friendly FISHING 410 is robustly constructed, made of corrosion-resistant aluminum and therefore extremely durable.,,Price ex works without motor, optional accessories and provision.,,ALL STATEMENTS WITHOUT GUARANTEE!
5th rowCasual fun boat for 6 people with undercarriage for the drive from beach to boat place.,,Swimming fun for the whole family in places that can only be reached by boat.,,Foldable bathing ladder for easy climbing out of the water. Space for igloo on platform. Folding sun / rain roof.,Drawbar for travel (walking pace) to winter storage / parking lot.,,Complete equipment with life jackets and all necessary utensils for the next check / acceptance
ValueCountFrequency (%)
the 8409
 
3.7%
and 6759
 
3.0%
5319
 
2.4%
with 5030
 
2.2%
in 4237
 
1.9%
to 2911
 
1.3%
for 2909
 
1.3%
a 2756
 
1.2%
of 2720
 
1.2%
boat 2646
 
1.2%
Other values (25367) 181775
80.6%
2023-08-24T15:33:19.711761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
223113
 
14.5%
e 129733
 
8.4%
t 95135
 
6.2%
a 91037
 
5.9%
i 86313
 
5.6%
o 84436
 
5.5%
r 81269
 
5.3%
n 79576
 
5.2%
s 62704
 
4.1%
l 50956
 
3.3%
Other values (114) 558477
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1092040
70.8%
Space Separator 223121
 
14.5%
Uppercase Letter 94547
 
6.1%
Other Punctuation 75578
 
4.9%
Decimal Number 41586
 
2.7%
Dash Punctuation 10103
 
0.7%
Close Punctuation 2093
 
0.1%
Open Punctuation 2079
 
0.1%
Math Symbol 1072
 
0.1%
Other Symbol 117
 
< 0.1%
Other values (8) 413
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 9000
 
9.5%
S 7911
 
8.4%
E 6954
 
7.4%
A 6816
 
7.2%
C 5947
 
6.3%
I 4865
 
5.1%
R 4738
 
5.0%
B 4437
 
4.7%
P 4432
 
4.7%
O 4093
 
4.3%
Other values (18) 35354
37.4%
Lowercase Letter
ValueCountFrequency (%)
e 129733
11.9%
t 95135
 
8.7%
a 91037
 
8.3%
i 86313
 
7.9%
o 84436
 
7.7%
r 81269
 
7.4%
n 79576
 
7.3%
s 62704
 
5.7%
l 50956
 
4.7%
c 41613
 
3.8%
Other values (16) 289268
26.5%
Other Punctuation
ValueCountFrequency (%)
, 47219
62.5%
. 14656
 
19.4%
: 4084
 
5.4%
/ 1864
 
2.5%
! 1548
 
2.0%
? 1370
 
1.8%
# 1106
 
1.5%
* 842
 
1.1%
; 765
 
1.0%
' 524
 
0.7%
Other values (9) 1600
 
2.1%
Decimal Number
ValueCountFrequency (%)
0 11135
26.8%
2 7472
18.0%
1 5328
12.8%
5 3314
 
8.0%
9 2839
 
6.8%
3 2733
 
6.6%
4 2719
 
6.5%
6 2148
 
5.2%
7 2039
 
4.9%
8 1859
 
4.5%
Control
ValueCountFrequency (%)
œ 53
68.8%
Ÿ 9
 
11.7%
– 6
 
7.8%
„ 4
 
5.2%
— 2
 
2.6%
“ 1
 
1.3%
˜ 1
 
1.3%
Â… 1
 
1.3%
Math Symbol
ValueCountFrequency (%)
+ 836
78.0%
> 116
 
10.8%
| 64
 
6.0%
= 43
 
4.0%
± 9
 
0.8%
< 2
 
0.2%
~ 2
 
0.2%
Modifier Symbol
ValueCountFrequency (%)
¨ 11
47.8%
` 5
21.7%
¸ 3
 
13.0%
´ 2
 
8.7%
^ 2
 
8.7%
Other Symbol
ValueCountFrequency (%)
© 63
53.8%
° 32
27.4%
® 21
 
17.9%
¦ 1
 
0.9%
Other Number
ValueCountFrequency (%)
¼ 96
88.1%
² 11
 
10.1%
³ 2
 
1.8%
Currency Symbol
ValueCountFrequency (%)
¤ 62
82.7%
¢ 10
 
13.3%
Â¥ 3
 
4.0%
Space Separator
ValueCountFrequency (%)
223113
> 99.9%
  8
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2079
99.3%
] 14
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 2065
99.3%
[ 14
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 10103
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 96
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 15
100.0%
Final Punctuation
ValueCountFrequency (%)
» 12
100.0%
Other Letter
ValueCountFrequency (%)
ª 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1186593
76.9%
Common 356156
 
23.1%

Most frequent character per script

Common
ValueCountFrequency (%)
223113
62.6%
, 47219
 
13.3%
. 14656
 
4.1%
0 11135
 
3.1%
- 10103
 
2.8%
2 7472
 
2.1%
1 5328
 
1.5%
: 4084
 
1.1%
5 3314
 
0.9%
9 2839
 
0.8%
Other values (59) 26893
 
7.6%
Latin
ValueCountFrequency (%)
e 129733
 
10.9%
t 95135
 
8.0%
a 91037
 
7.7%
i 86313
 
7.3%
o 84436
 
7.1%
r 81269
 
6.8%
n 79576
 
6.7%
s 62704
 
5.3%
l 50956
 
4.3%
c 41613
 
3.5%
Other values (45) 383821
32.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1541731
99.9%
None 1018
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
223113
14.5%
e 129733
 
8.4%
t 95135
 
6.2%
a 91037
 
5.9%
i 86313
 
5.6%
o 84436
 
5.5%
r 81269
 
5.3%
n 79576
 
5.2%
s 62704
 
4.1%
l 50956
 
3.3%
Other values (82) 557459
36.2%
None
ValueCountFrequency (%)
à 387
38.0%
 122
 
12.0%
¼ 96
 
9.4%
© 63
 
6.2%
¤ 62
 
6.1%
œ 53
 
5.2%
¶ 35
 
3.4%
° 32
 
3.1%
· 25
 
2.5%
® 21
 
2.1%
Other values (22) 122
 
12.0%

Equipment
Text

MISSING 

Distinct5301
Distinct (%)85.9%
Missing4170
Missing (%)40.3%
Memory size80.9 KiB
2023-08-24T15:33:20.223597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length798
Median length520
Mean length176.06608
Min length3

Characters and Unicode

Total characters1087032
Distinct characters86
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4933 ?
Unique (%)79.9%

Sample

1st rowAnchor,Battery,Bilge Pump,Bilge pump,Cockpit Cover,Compass,Depth Instrument,Gas Stove,Stern Thruster,Teak Cockpit,Teak Deck,Underwater Paint
2nd rowAnchor,Mooring Cover,Swim Ladder,Trailer
3rd rowFull Enclosure
4th rowCompass,Fire Extinguisher,Full Enclosure,Radio,Speed Instrument,Swim Ladder
5th rowBattery
ValueCountFrequency (%)
charger,bilge 2685
 
4.3%
instrument,fm 1898
 
3.0%
pump,bimini 1591
 
2.5%
air 1530
 
2.4%
radio,fire 1324
 
2.1%
shower,depth 1278
 
2.0%
anchor 1210
 
1.9%
thruster,cd 1058
 
1.7%
ladder,teak 1013
 
1.6%
instrument 964
 
1.5%
Other values (4779) 48242
76.8%
2023-08-24T15:33:21.398218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 100077
 
9.2%
r 89155
 
8.2%
, 88455
 
8.1%
t 78671
 
7.2%
o 63654
 
5.9%
i 63349
 
5.8%
a 59677
 
5.5%
56621
 
5.2%
n 50096
 
4.6%
s 29463
 
2.7%
Other values (76) 407814
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 775634
71.4%
Uppercase Letter 164973
 
15.2%
Other Punctuation 88631
 
8.2%
Space Separator 56621
 
5.2%
Decimal Number 622
 
0.1%
Dash Punctuation 249
 
< 0.1%
Other Symbol 98
 
< 0.1%
Control 69
 
< 0.1%
Other Number 54
 
< 0.1%
Currency Symbol 47
 
< 0.1%
Other values (5) 34
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 100077
12.9%
r 89155
11.5%
t 78671
10.1%
o 63654
 
8.2%
i 63349
 
8.2%
a 59677
 
7.7%
n 50096
 
6.5%
s 29463
 
3.8%
l 26829
 
3.5%
p 26460
 
3.4%
Other values (16) 188203
24.3%
Uppercase Letter
ValueCountFrequency (%)
C 22395
13.6%
B 20100
12.2%
S 17012
10.3%
P 15433
9.4%
T 11721
 
7.1%
R 10735
 
6.5%
D 9843
 
6.0%
F 8977
 
5.4%
A 8495
 
5.1%
I 7799
 
4.7%
Other values (16) 32463
19.7%
Decimal Number
ValueCountFrequency (%)
3 464
74.6%
2 61
 
9.8%
0 32
 
5.1%
1 26
 
4.2%
5 13
 
2.1%
4 11
 
1.8%
9 6
 
1.0%
8 5
 
0.8%
6 3
 
0.5%
7 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 88455
99.8%
/ 58
 
0.1%
. 54
 
0.1%
¶ 31
 
< 0.1%
' 24
 
< 0.1%
& 6
 
< 0.1%
% 2
 
< 0.1%
: 1
 
< 0.1%
Control
ValueCountFrequency (%)
Ÿ 32
46.4%
‰ 23
33.3%
– 14
20.3%
Other Symbol
ValueCountFrequency (%)
© 97
99.0%
® 1
 
1.0%
Currency Symbol
ValueCountFrequency (%)
¤ 44
93.6%
¢ 3
 
6.4%
Modifier Symbol
ValueCountFrequency (%)
¨ 7
50.0%
´ 7
50.0%
Space Separator
ValueCountFrequency (%)
56621
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 249
100.0%
Other Number
ValueCountFrequency (%)
¼ 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Letter
ValueCountFrequency (%)
ª 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 940608
86.5%
Common 146424
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 100077
 
10.6%
r 89155
 
9.5%
t 78671
 
8.4%
o 63654
 
6.8%
i 63349
 
6.7%
a 59677
 
6.3%
n 50096
 
5.3%
s 29463
 
3.1%
l 26829
 
2.9%
p 26460
 
2.8%
Other values (43) 353177
37.5%
Common
ValueCountFrequency (%)
, 88455
60.4%
56621
38.7%
3 464
 
0.3%
- 249
 
0.2%
© 97
 
0.1%
2 61
 
< 0.1%
/ 58
 
< 0.1%
. 54
 
< 0.1%
¼ 54
 
< 0.1%
¤ 44
 
< 0.1%
Other values (23) 267
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1086404
99.9%
None 628
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 100077
 
9.2%
r 89155
 
8.2%
, 88455
 
8.1%
t 78671
 
7.2%
o 63654
 
5.9%
i 63349
 
5.8%
a 59677
 
5.5%
56621
 
5.2%
n 50096
 
4.6%
s 29463
 
2.7%
Other values (62) 407186
37.5%
None
ValueCountFrequency (%)
à 313
49.8%
© 97
 
15.4%
¼ 54
 
8.6%
¤ 44
 
7.0%
Ÿ 32
 
5.1%
¶ 31
 
4.9%
‰ 23
 
3.7%
– 14
 
2.2%
¨ 7
 
1.1%
´ 7
 
1.1%
Other values (4) 6
 
1.0%

Interactions

2023-08-24T15:32:20.210879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:10.284069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:12.310418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:14.505714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:16.348123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:18.131551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:20.558770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:10.598968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-08-24T15:32:14.878592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-08-24T15:32:20.953641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-08-24T15:32:13.041185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:15.162501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:16.948927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:18.860312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:21.323522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:11.276750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:13.379075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:15.447408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:17.237836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:19.212199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:21.658414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:11.638634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:13.755954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:15.758309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:17.514745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:19.565086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:21.983313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:11.974527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:14.109839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:16.060213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:17.786657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-24T15:32:19.887983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-08-24T15:33:21.749103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Year BuiltCert Number of PeopleNumber of CabinsNumber of bedsNumber of ToiletsNumber of ShowersTypeConditionCE Design CategoryNumber of BathroomsMaterialPropulsionFuel Type
Year Built1.000-0.007-0.051-0.026-0.1010.0720.2060.2980.2560.0000.2040.1650.113
Cert Number of People-0.0071.0000.5110.4140.4220.2070.0001.0001.0001.0001.0001.0000.000
Number of Cabins-0.0510.5111.0000.7650.7760.5760.0000.0001.0001.0000.0390.0000.000
Number of beds-0.0260.4140.7651.0000.5810.5350.1930.1460.3080.4050.0360.3740.259
Number of Toilets-0.1010.4220.7760.5811.0000.8810.0000.0000.0000.0000.0290.0000.000
Number of Showers0.0720.2070.5760.5350.8811.0000.0810.1080.2760.0000.0870.2940.160
Type0.2060.0000.0000.1930.0000.0811.0000.3130.3760.1690.2460.3560.999
Condition0.2981.0000.0000.1460.0000.1080.3131.0000.2700.0000.1090.1840.163
CE Design Category0.2561.0001.0000.3080.0000.2760.3760.2701.0000.1100.2650.2470.336
Number of Bathrooms0.0001.0001.0000.4050.0000.0000.1690.0000.1101.0000.1660.1580.215
Material0.2041.0000.0390.0360.0290.0870.2460.1090.2650.1661.0000.1960.132
Propulsion0.1651.0000.0000.3740.0000.2940.3560.1840.2470.1580.1961.0000.337
Fuel Type0.1130.0000.0000.2590.0000.1600.9990.1630.3360.2150.1320.3371.000

Missing values

2023-08-24T15:32:22.713078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-24T15:32:24.651453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-08-24T15:32:27.301605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

PriceCategoryBoat TypeManufacturerModelBoat nameTypeYear BuiltConditionLengthWidthDepthDisplacementCE Design CategoryCert Number of PeopleNumber of CabinsNumber of bedsHull ColorNumber of ToiletsNumber of BathroomsNumber of ShowersMaterialFresh Water CapHolding TankPropulsionEngineEngine PerformanceFuel CapacityFuel TypeEngine HoursMax SpeedCruising SpeedLocationAdvertisement DateNumber of views last 7 daysCommentsAdditional CommentsEquipment
0CHF 3.337,-Power BoatsMotor YachtRigiflex power boatsCAP 400NaNnew boat from stock2017.0as new4.00 m1.90 mNaNNaNNaN7.0NaNNaNwhiteNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSwitzerland » Lake Geneva » VésenazNaN226NaNPossibility to arrange it with a complete luxury kit (bench box with upholstery, side console, front balconies),,Price on requestNaN
1EUR 3.490,-Power BoatsCenter console boatTerhi power boats400 CNaNnew boat from stock2020.0new4.00 m1.50 mNaN150 kgNaNNaNNaNNaNNaNNaNNaNNaNThermoplasticNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNGermany » BönningstedtNaN75In den Farben weiß oder grün lieferbar.,,2 abschließbare Staufächer, 3 Sitzbänke, Spiegelplatte, Scheuerleiste, Selbstlenzventil. Wie Terhi 400 zusätzlich Seitensteuerkonsole mit mech. Steuerung (ohne Riemen, Dollen Dollenhalterungen).,,Zusätzliche Ausstattung:,,Das stabile und sichere Terhi 400 C ist mit einem Steuerstand ausgestattet und als Sport- und Freizeitboot für ein bis vier Personen auf Seen oder geschützten Meeresgebieten geeignet. Gleichzeitig ist das Boot ein guter Begleiter für Sportangler. Das Boot hat beste Fahreigenschaften über die komplette Geschwindigkeitsskala selbst mit einem kleinen Motor. Zudem ist es einfach zu slippen und zu trailern. Abschließbare Backskisten im Bug und Heck bieten darüber hinaus praktischen Stauraum. Sie können das Boot für Ihren Verwendungszweck mit Zubehör individualisieren, zum Beispiel mit einer Windschutzscheibe für den Steuerstand und Relingsätzen oder mit einer gepolsterten Liegefläche für den Bugbereich.,,Preis ab Werk zzgl. Vorfracht,,Gerne erstellen wir Ihnen ein persönliches Angebot und freuen uns auf,Ihre Kontaktaufnahme.,,Bilder können Sonderoptionen zeigen. Irrtum vorbehalten.,,,,www.gruendl.deNaNNaN
2CHF 3.770,-Power BoatsSport BoatMarine power boats370 S - AlubootNaNnew boat from stockNaNNaN3.69 m1.42 m0.25 mNaNNaN4.0NaNNaNNaNNaNNaNNaNAluminiumNaNNaNNaN(Permission for Lake of Constance)NaNNaNNaNNaNNaNNaNSwitzerland » Lake of Zurich » Stäfa ZHNaN124NaNThe lightweight and sleek rowing boat for 4 people is very easy to clean and suitable for the drying area. It can be equipped with an outboard motor to 15 hp. (Examination free to 8 hp).,As an option, there are a lot of accessories like bathing ladder, sun shade, floor mats, different sizes of seat rowing and more.,You can find more 20 different boat models in the permanent boat show of Bootbau Huber AG, Stäfa. www.boot-bau.chNaN
3DKK 25.900,-Power BoatsSport BoatPioner power boats10 Classic Special EditionNaNnew boat from stock2020.0NaN3.00 m1.00 mNaN110 kgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNDenmark » SvendborgNaN64MORSOM OG LETKØRT KVALITETSBÅD!,Nye Pioner 10 Classic er en snerten og sikker båd som er let at håndtere og manøvrere ? og som passer perfekt for barn og voksne.,,Den moderne model er selvdrenerende, solid, letplanende og fin at ro. Pioner 10 Classic føles vældig tryg og er samtidig egnet til mange forskellige brugsområder, nogle både store og små vil sætte pris på. Båden har plads til tre personer og er godkendt for 9.9 Hk.,,,,,,,Farver:,,Leif Larsens Special Edition version med lav konsol, ræling agter, badestige, Yamaha F9.9 Vmax Sport m. el-start og fjernbetjening, sejlklar tilbud Kr. 54.500,-!NaNNaN
4SEK 35.000,-Power BoatsClassicNaNGullholmensnipa 21NaNUsed boat1974.0good6.30 m2.50 m0.75 m2'000 kgNaNNaNNaN2.0NaNNaNNaNNaNNaNNaNNaNInboard with ShaftVolvoPenta MD 20021 x 18 HP / 13 kW50 lNaN500 hNaNNaNNordsee » Västra Frölunda04.07.2020131NaNNaNAnchor,Battery,Bilge Pump,Bilge pump,Cockpit Cover,Compass,Depth Instrument,Gas Stove,Stern Thruster,Teak Cockpit,Teak Deck,Underwater Paint
5EUR 3.399,-Power BoatsFishing BoatLinder power boats355 SportsmanNaNnew boat from stock2019.0new3.55 m1.46 mNaN84 kgNaN4.0NaNNaNNaNNaNNaNNaNAluminiumNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNGermany » Bayern » MünchenNaN58NaNFor engines up to Type 8, the environmentally friendly boat is made of high quality, corrosion resistant,Aluminum made, as it is also used for aircraft construction,becomes. Sportsman 355 comes with aluminum rudders. The boat is from Det Norske,Veritas and has a Securmark anti-theft tag *.,SPORTSMAN 355 A gliding boat type for inland lakes and rivers.NaN
6CHF 3.650,-Power BoatsSport BoatLinder power boatsFishing 410 (Aluminiumboot)NaNnew boat from stockNaNNaN4.03 m1.56 mNaN75 kgNaN3.0NaNNaNNaNNaNNaNNaNAluminiumNaNNaNNaN(Permission for Lake of Constance)NaNNaNNaNNaNNaNNaNSwitzerland » Lake Constance » UttwilNaN132NaNA light rowing boat with rib profile for inland lakes. Can be used with smaller outboard motors or electric motors up to max. Equip 2.5 hp.,,FISHING 410 comes with aluminum rudders and rescue ladder.,,The environmentally friendly FISHING 410 is robustly constructed, made of corrosion-resistant aluminum and therefore extremely durable.,,Price ex works without motor, optional accessories and provision.,,ALL STATEMENTS WITHOUT GUARANTEE!NaN
7CHF 3.600,-Power BoatsCatamaranNaNStoll SA YverdonNaNUsed boat,Unleaded1999.0well-groomed6.20 m2.38 m0.40 m350 kgNaN6.0NaNNaNNaNNaNNaNNaNAluminiumNaNNaNOutboard, four-strokeYamaha F8 BMH 5.6 kWNaN40 lUnleadedNaNNaNNaNSwitzerland » Neuenburgersee » Yvonand02.06.2020474NaNCasual fun boat for 6 people with undercarriage for the drive from beach to boat place.,,Swimming fun for the whole family in places that can only be reached by boat.,,Foldable bathing ladder for easy climbing out of the water. Space for igloo on platform. Folding sun / rain roof.,Drawbar for travel (walking pace) to winter storage / parking lot.,,Complete equipment with life jackets and all necessary utensils for the next check / acceptanceAnchor,Mooring Cover,Swim Ladder,Trailer
8DKK 24.800,-Power BoatsSport BoatNaNCrazy OneNaNUsed boatNaNNaN3.00 mNaNNaN75 kgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1 x 15 HP / 11 kW1 x 15 HP / 11 kWNaNNaNNaNNaNNaNDenmark » SvendborgNaN134Crazy One´s elegante og spændende design kombinerer facinerende "motorcykel-egenskaber" med et dybt og tørt cockpit til 2 personer.,,Linieføring og udformning under vandlinien går Crazy One sjov og let at sejle, giver udfordring og spænding til race, vandski, fiskeri og som ledsagerfartøj - Den ideelle fritidsbåd for hele familien.,,Den lave vægt sikrer et sparsomt brændstofsforbrug og let håndtering på biltag, påhængsvogn, bådtrailer eller bag på en større motorbåd. Båden er udstyret med 15 hk 4-takts motor årgang 2010, sejlet minimalt af timer.NaNNaN
9EUR 3.333,-Power BoatsFishing BoatCrescent power boats364 Rodd 2.5 PackNaNnew boat from stock2019.0NaN3.64 m1.37 mNaN77 kgNaNNaNNaNNaNwhite whiteNaNNaNNaNNaNNaNNaNOutboard, four-strokeSuzuki DF 2.51 x 2 HP / 1.5 kWNaNNaNNaNNaNNaNGermany » Bayern » Boote+service OberbayernNaN45NaNtogether with 2 wooden rudders, 3 wooden benches and full tarpaulin,,Of course, also available with electric motor, ask us for the priceFull Enclosure
PriceCategoryBoat TypeManufacturerModelBoat nameTypeYear BuiltConditionLengthWidthDepthDisplacementCE Design CategoryCert Number of PeopleNumber of CabinsNumber of bedsHull ColorNumber of ToiletsNumber of BathroomsNumber of ShowersMaterialFresh Water CapHolding TankPropulsionEngineEngine PerformanceFuel CapacityFuel TypeEngine HoursMax SpeedCruising SpeedLocationAdvertisement DateNumber of views last 7 daysCommentsAdditional CommentsEquipment
10334CHF 4.990,-Power BoatsSport BoatPioner power boats14 ActiveNaNnew boat on orderNaNnew4.11 m1.73 mNaN220 kgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSwitzerland » SafenwilNaN280NaNPioner 14 Active,,Catalog price: CHF 4 \ '990.- incl.VAT,,Ready to drive boat with Yamaha F8FMHS engine: CHF 8 \ '100.- incl.VAT,Ready to drive boat with Yamaha F20GMHS engine: CHF 9 \ '300.- incl.VAT,,Max. Motorization: 20HP,,Prices valid from Safenwil!,Sales exclusively through our CH dealer network!NaN
10335CHF 4.980,-Power BoatsSport BoatLinder power boatsSportsman 400 (Aluminiumboot)NaNnew boat from stockNaNNaN4.01 m1.64 mNaN125 kgNaN4.0NaNNaNNaNNaNNaNNaNAluminiumNaNNaNNaN(Permission for Lake of Constance)NaNNaNNaNNaNNaNNaNSwitzerland » Lake Constance » UttwilNaN247NaNA gliding family boat for inland lakes and offshore waters suitable for sport fishing and water skiing. Can be used with an outboard motor up to max. Equip 20 hp.,,The environmentally friendly SPORTSMAN 400 is robustly constructed, made of corrosion-resistant aluminum and therefore extremely durable.,,Storage compartment in aft and center benches, control console (accessory) with space for the battery. SPORTSMAN 400 comes with aluminum rudders and rescue ladder.,,Price ex works without motor, optional accessories and provision.,,ALL STATEMENTS WITHOUT GUARANTEE!NaN
10336CHF 4.950,-Power BoatsSport BoatMarine power boats400 U - AlubootNaNnew boat from stockNaNNaN3.99 m1.52 m0.20 m85 kgNaNNaNNaNNaNNaNNaNNaNNaNAluminiumNaNNaNNaN(Permission for Lake of Constance)NaNNaNNaNNaNNaNNaNSwitzerland » Lake of Zurich » Stäfa ZHNaN150NaNThe ideal recreational boat suitable for water stand as for the drying area. Achieved with non-testing engines up to 25 km / h. The boat can be motorize to 20 PS and has capacity for 6 people. Desire to the price list of the accessories and engine or visit the permanent exhibition of boat Bootbau Huber AG, Seestrasse 197, 8712 Stäfa. ####@boot-bau.ch Tel. 044 926 25 25NaN
10337CHF 4.950,-Power BoatsFishing BoatStaempfli power boats622NaNUsed boat,Unleaded1984.0well-groomed6.00 m1.62 mNaNNaNNaN6.0NaNNaNNaNNaNNaNNaNPlasticNaNNaNOutboard, four-strokeHonda BF8D41 x 8 HP / 5.9 kWNaNUnleadedNaNNaNNaNSwitzerland » Bielersee » Gerolfingen30.05.2020288NaN2013 engine,Trailer without MFK,Incl. Fishing and accessories,From place without guaranteeFull Enclosure,Trailer
10338CHF 4.900,-Power BoatsSport BoatSea Ray power boatsMonaco 200NaNUsed boat,Unleaded1987.0used6.30 m2.44 mNaNNaNNaN6.0NaNNaNNaNNaNNaNNaNNaNNaNNaNSterndriveOMC 5741 x 264 HP / 194 kWNaNUnleadedNaNNaNNaNSwitzerland » Lago Maggiore » RiazzinoNaN1'116NaNNaNNaN
10339EUR 4.516,-Power BoatsSport BoatNaNFOX BOATS 420C ECNaNnew boat from stockNaNNaN4.17 m1.68 mNaN185 kgNaNNaNNaNNaNNaNNaNNaNNaNGRPNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNGermany » Hamburg » HAMBURGNaN94Länge: 4,17m | Breite: 1,67m | max. Motorisierung: 22 kW (30 PS) | Bordwandhöhe: 0,6m | zul. Ges.-Gewicht: 515 kg | Leergewicht: 185 kg | max. Zuladung: 300/385 kg | max. Personenzahl: 4/5 | Kategorie: C/D | Aufkimmung: 11°,Boot in Grundausstattung,Der Herrsteller Fox Boats hat sich zum Ziel gesetzt, durch Kooperation von Bootsbauern und erfolgreichen Sportfischern Boote zu bauen, welche genau auf die Bedürfnisse der Sportfischer zugeschnitten sind. Das neueste Produkt dieses Entwicklungskonzepts ist das Fox 420C. An seinem komfortablen Steuerstand, den vielen Staumöglichkeiten und durchdachten Extras wie dem integrierten Köderfischbecken ist die durchdachte Orientierung an den Anforderungen der Angler zu erkennen. Das geringe Leergewicht von nur 185 kg ermöglicht es, das Boot auch mit kleinen Zugfahrzeugen komfortabel auf einem Trailer zu ziehen.,Inkl . Ausstattung plus Transport Kosten,* Trailer auf Anfrage,,--- Zwischenverkauf und Irrtümer vorbehalten ---NaNNaN
10340EUR 4.499,-Power BoatsSport BoatBlueCraft power boatsBlueSloep 140NaNnew boat from stock,Unleaded2020.0NaN4.40 m1.80 m0.22 mNaNNaN5.0NaNNaNblack wie gewünschtNaNNaNNaNGRPNaNNaNNaN(Permission for Lake of Constance)NaN12 lUnleadedNaNNaNNaNGermany » Nordrhein-Westfalen » WeselNaN354NaNThe BlueSloep 140 is the smallest boat in the BlueSloep family. The boat is for families,thought and at the same time adapted to the needs of the fishing enthusiasts. By in the middle,Placed helm, the small enough space for all passengers. The port and,Starboard treads make it easier to get in and out on the shore or in the harbor. The big,Backbox at the rear and the 2 side storage compartments provide plenty of storage space. The Sundeck (optional),in the bow area, invites you to relax after a hard day's fishing or after a trip.,,Technical data and design:,,- Length: 4,40m,- Width: 1,80m,- Weight: 215Kg,- Category C,- all seat and back cushions,- rubbing strip with dewing ring,- Stainless steel cleats,,,,Complete packages with engine and trailer, just inquire! Pick up warehouse Wesel.,Photos are sample photos and may contain elements that are not part of the offer!,,We carry pleasure boats, cabin boats, fishing boats, console boats, PE boats, inflatable boats, ribs, outboard Suzuki and Mercury, as well as the complete range of accessories. Sightseeing / Exhibition: We are open daily from 9:30 am to 6:00 pm and Saturday from 9:00 am to 1:00 pm. Workshop dates please in consultation 0281-47363720!,,BlueCraft GmbH - Rudolf Diesel Straße 114 - 46485 Wesel (new building),,We lead:,Italmar,Ocean Master,BlueLiner,BlueRibs,BlueSloep,BlueCraft inflatable boats,Rigiflex,Suzuki,Mercury,Allpa,Osculati,Trailer,and much more.,,* Photos may contain other features that are not part of this offer.NaN
10341EUR 4.300,-Power BoatsPontoon BoatWhaly power boats450 New ClassicNaNnew boat from stock2018.0new4.37 m1.89 mNaN340 kgNaN8.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNItaly » DormellettoNaN266Caratteristiche tecniche,,Materiale: Polietilene Rotazionale,Motorizzazione: Gambo lungo,Lunghezza: 4,37 mt.,Larghezza: 1,89 mt,Altezza: 1,05 mt.,Altezza specchio di poppa: 0,67 mt.,Peso: 340 kg.,Capacità (persone): CE Cat. D 8 pers. - Cat C 4 pers,Peso massimo: CE Cat. D 800 kg. - Cat C 550 kg. (compreso motore),Potenza massima: 2 Kw elettrico - 6 CV (4,4 kw) - CE 8 cv (5,9 kw),Colorazioni: Rosso, Grigio, Giallo, Blu, Arancio, Nero, Grigio scuro, Verde e Marrone,Accessori: Timoneria,,Le imbarcazioni Whaly sono realizzate interamente con doppia parete plastica (PE) in unico pezzo e prodotte mediante la tecnica dello stampaggio rotazionale.,La progettazione, il metodo di produzione e la plastica polietilene di elevata qualità costituiscono le basi per imbarcazioni ultraresistenti, inaffondabili, indistruttibili e con necessità di manutenzione minima, caratterizzate da grande spazio interno, sicurezza e stabilità.,,Tutti i modelli Whaly 210, 270, 310, 370, 435 e 450 Classic si prestano ottimamente al settore ricreativo, mentre i modelli 310, 370 e 435 sono multifunzionali e sono perfetti a fini professionali. Nei modelli Whaly ad uso professionale sono fondamentalii requisiti, spesso estremi, posti dal cliente: una scuola di vela, ad esempio, desidera un’imbarcazione guida stabile, sicura e resistente e nell’ambito della navigazione professionale le imbarcazioni Whaly sono utilizzate come mezzi di salvataggio a bordo, con certificazione 94/25/EG, 2003/44/EG e NEN-EN 1914 (opzionale).,,Nei modelli ad uso ricreativo, l’accento sempre posto sulla navigazione sicura e stabile, ma un occhio riservato anche allo styling, alla comodità d’uso e al comfort senza tralasciare sicurezza, affidabilità e durata.,,Grazie a simili caratteristiche, le imbarcazioni Whaly trovano diversi campi d’applicazione:,,Navigazione da diporto,Imbarcazione da lavoro,Natante di salvataggio,Pesca sportiva,Noleggio,Scuole nautiche,,Accessori optional: Consolle, remi, rollbar, tendalino, cuscineria e telo copertura totale.NaNNaN
10342EUR 3.500,-Power BoatsSport BoatFletcher power boatsBravoNaNUsed boat,Unleaded1992.0good4.27 m1.60 mNaN270 kgC - Inshore4.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMariner 40 hp1 x 40 HP / 29 kW30 lUnleaded10 hNaNNaNHungary » Ebes23.07.2020NaNTrailer comes with two new tyres and new wheel bearings, detachable trailer lights also included. I used this boat in UK and Croatia without any problems. Engine comes with two locks so that no one can steal it. I took it out yesterday 23rd July 2020 from my garage and started it with no problem at all. If any questions please do not hesitate to contact me and the price is negotiable.NaNBattery,Fire Extinguisher,Full Enclosure,Speed Instrument,Trailer
10343CHF 3.780,-Power BoatsFishing BoatDarekCo power boatsTexas 360NaNnew boat from stock2019.0new3.60 m1.60 mNaNNaNNaN4.0NaNNaNwhiteNaNNaNNaNGRPNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSwitzerland » Brienzersee » BrienzNaN194NaNRowing and fishing boat in robust GFK laminate construction. Two lockable storage compartments are integrated in the bow and rear bench.,The standard version includes the following accessories:,- Rudder,- Handrail,- 3 mooring rings,- Cleat,- acrylic cover f. Winter camp,The boat is up to max. 15 hp motorized.NaN

Duplicate rows

Most frequently occurring

PriceCategoryBoat TypeManufacturerModelBoat nameTypeYear BuiltConditionLengthWidthDepthDisplacementCE Design CategoryCert Number of PeopleNumber of CabinsNumber of bedsHull ColorNumber of ToiletsNumber of BathroomsNumber of ShowersMaterialFresh Water CapHolding TankPropulsionEngineEngine PerformanceFuel CapacityFuel TypeEngine HoursMax SpeedCruising SpeedLocationAdvertisement DateNumber of views last 7 daysCommentsAdditional CommentsEquipment# duplicates
0EUR 4.000,-Power BoatsLaunchNaNZaccagnino ANACONDANaNUsed boat1984.0NaN6.00 m2.20 mNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNGRPNaNNaNNaNBuck1 x 20 HP / 15 kW50 lNaNNaNNaNNaNItaly » Toscana » ToscanaNaNNaNNaNNaNNaN2